# HG changeset patch
# User Me@portablequad
# Date 1328214028 28800
# Node ID bc4dd419ed1acbe8d932ec3d147461786af1d6e2
# Parent  e455dad927457c4f2b93ddd48d5d29c7dff90c1b
Submitted version of HotPar 2012  PStack + VMS paper

diff -r e455dad92745 -r bc4dd419ed1a 0__Papers/VMS/VMS__Foundation_Paper/HotPar_2012/figures/Portability_stack_combined.eps
--- a/0__Papers/VMS/VMS__Foundation_Paper/HotPar_2012/figures/Portability_stack_combined.eps	Tue Jan 31 18:03:47 2012 -0800
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,7168 +0,0 @@
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-h
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diff -r e455dad92745 -r bc4dd419ed1a 0__Papers/VMS/VMS__Foundation_Paper/HotPar_2012/figures/Time_layers.eps
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diff -r e455dad92745 -r bc4dd419ed1a 0__Papers/VMS/VMS__Foundation_Paper/HotPar_2012/latex/12_Ja_20__HotPar_Abstr_for_PStack.pdf
Binary file 0__Papers/VMS/VMS__Foundation_Paper/HotPar_2012/latex/12_Ja_20__HotPar_Abstr_for_PStack.pdf has changed
diff -r e455dad92745 -r bc4dd419ed1a 0__Papers/VMS/VMS__Foundation_Paper/HotPar_2012/latex/12_Ja_20__HotPar_Abstr_for_PStack.tex
--- a/0__Papers/VMS/VMS__Foundation_Paper/HotPar_2012/latex/12_Ja_20__HotPar_Abstr_for_PStack.tex	Tue Jan 31 18:03:47 2012 -0800
+++ b/0__Papers/VMS/VMS__Foundation_Paper/HotPar_2012/latex/12_Ja_20__HotPar_Abstr_for_PStack.tex	Thu Feb 02 12:20:28 2012 -0800
@@ -86,9 +86,9 @@
 \begin{abstract}
 The HotPar 2012 call for papers states that wide uptake of high efficiency parallel architectures ``requires new parallel programming paradigms, new methods of application design, new structures for system software, and new models of interaction among applications, compilers, operating systems, and hardware." In short, a new software stack, and a way to organize players in research and industry to  supply the pieces of the stack.
 
-A recent proposal for a candidate for such a software stack\cite{} relies in part on the assumption that a suitable hardware abstraction exists for the bottom layer of the stack. The abstraction's main purpose is to reduce the effort required in the upper layers. It must reduce the effort of creating language runtimes: by hiding details of synchronization and communication; by regularizing implementation to simplify and encourage reuse across languages; and by reducing the number of runtimes needed by collecting multiple targets below a single interface. It must at the same time enable high performance, by giving the  language control over task placement and exposing to the runtime the memory hierarchy, communication characteristics, and other major performance-related aspects of the hardware.
+A recently proposed candidate for such a software stack\cite{PStackHome} relies in part on the assumption that a suitable hardware abstraction exists for the bottom layer of the stack. The abstraction's main purpose is to reduce the effort required in the upper layers. It must reduce the effort of creating language runtimes: by hiding details of synchronization and communication; by regularizing implementation to simplify and encourage reuse across languages; and by reducing the number of runtimes needed by collecting multiple targets below a single interface. It must at the same time enable high performance, by giving the  language control over task placement and exposing to the runtime's scheduler the memory hierarchy, communication characteristics, and other major performance-related aspects of the hardware.
 
-In this paper, we show that an abstraction called Virtualized Master-Slave, or VMS \cite{} satisfies these criteria, and we provide recent measurements to support the case.
+In this paper, we show that an abstraction called Virtualized Master-Slave, or VMS \cite{VMSHome} satisfies these criteria, and we provide recent measurements to support the case.
 
 \end{abstract}
 
@@ -97,13 +97,13 @@
 \section{Motivation}
 
 
-As stated in the call for papers, wide uptake of high efficiency parallel architectures ``requires new parallel programming paradigms, new methods of application design, new structures for system software, and new models of interaction among applications, compilers, operating systems, and hardware." Each of which is an element of the software stack, which is normally supplied by multiple players in research and industry. They need to be organized to supply the pieces of the stack.
+As stated in the call for papers, wide uptake of high efficiency parallel architectures ``requires new parallel programming paradigms, new methods of application design, new structures for system software, and new models of interaction among applications, compilers, operating systems, and hardware." Which are element of the software stack, and normally supplied by multiple players in research and industry. The players need to be organized to supply the pieces of the stack.
 
 The goal of the stack is  to make parallel programming as productive as sequential programming, and to make it as portable onto new generations of hardware as sequential code.
 
 Reduced  cost of parallel software is one major benefit of such a stack. Part of the cost reduction comes from  performant portability.  This means  code is written once then run performantly across hardware targets, including unknown future architectures.
 
-A recent proposal for achieving this, named PStack\cite{},  calls for a software stack having a layer of languages (toolchains) at the top, a layer of runtimes below that, and a hardware abstraction layer at the bottom.
+A recent proposal for achieving this, named PStack\cite{PStackHome},  calls for a software stack having a layer of languages (toolchains) at the top, a layer of runtimes below that, and a hardware abstraction layer at the bottom.
 
 It is this bottom layer that we focus on in this paper.  We begin by giving context for the bottom layer with more information about the software stack, in Section 2. We then explore the requirements for the layers in in Section 3, and show how VMS satisfies the requirements in Section 4.  We then move to results, giving our experimental setup in Section 5, and measurements in Section 6.  In Section 7 we tie the elements of the paper together in the conclusion.
 
@@ -111,7 +111,7 @@
 %%%%%%%%%%%%%%%%%%%%%
 \section{Context:  PStack}
 
-Many projects are attempting portability \cite{}. PStack differentiates itself in three ways: 1) it's goal is wider than most: (nearly) all-languages to (nearly) all hardware 2) It's approach is to \emph{organize} -- industry supplies the pieces of the solution, while PStack itself only provides the interfaces and scaffolding, along with  the seed of a solution to start 3) PStack has unique approaches for the application interface and the hardware interface that fill fundamental needs.
+Many projects are attempting portability \cite{OpenMPHome,TBBHome,OpenCLHome,Sequioa06,SEJITS}. PStack differentiates itself in three ways: 1) it's goal is wider than most: (nearly) all-languages to (nearly) all hardware 2) It's approach is to \emph{organize} -- industry supplies the pieces of the solution, while PStack itself only provides the interfaces and scaffolding, along with  the seed of a solution to start 3) PStack has unique approaches for the application interface and the hardware interface that fill fundamental needs.
 
 The general philosophy is that portability involves too much effort to be solved by a single group.  Instead, an industry-wide effort is needed, where each player provides one small piece of the solution.  This, though, requires some way to organize it all, and modularize the pieces.
 
@@ -148,11 +148,11 @@
 Although the paper focuses on the bottom abstraction,  its requirements are influenced by the layers above. So we present a full picture of the requirements in the stack, to give a complete picture for the bottom abstraction. 
 
 \subsection{Top Layer: Language Requirements}
-The languages must be designed to capture all information required to specialize the source for high performance on any target hardware. A computation model, called The Holistic Model\cite{}, suggests that such a canonical set of information exists. 
+The languages must be designed to capture all information required to specialize the source for high performance on any target hardware. A computation model, called The Holistic Model\cite{HolisticHome}, suggests that such a canonical set of information exists. 
 
-PStack proposes to develop the constructs that gather the canonical information set, where some constructs are in the form of specialization helpers such as task-resizers and layout modifiers. The application implements the specialization helpers, thereby encoding information about data structures and how to manipulate them.  The seeds of such an approach were laid with work on DKU\cite{}, which demonstrated the success of task-resizing constructs.
+PStack proposes to develop the constructs that gather the canonical information set, where some constructs are in the form of specialization helpers such as task-resizers and layout modifiers. The application implements the specialization helpers, thereby encoding information about data structures and how to manipulate them.  The seeds of such an approach were laid with work on DKU\cite{DKUSourceForge}, which demonstrated the success of task-resizing constructs.
 
-PStack also calls for the use of the BLIS\cite{} approach for managing multiple toolchains, where each toolchain specializes to a different target. The management covers the  install process, during which the correct toolchain output is paired to the installation target.  Further specialization can thus be naturally added during installation, when exact hardware details are known.  If required, runtime tuning and optimization also fit naturally  within the approach.
+PStack also calls for the use of the BLIS\cite{BLISHome} approach for managing multiple toolchains, where each toolchain specializes to a different target. The management covers the  install process, during which the correct toolchain output is paired to the installation target.  Further specialization can thus be naturally added during installation, when exact hardware details are known.  If required, runtime tuning and optimization also fit naturally  within the approach.
 
 \subsection{Middle Layer: Runtime Requirements}
 
@@ -191,8 +191,6 @@
 
 VMS is invisible to the application, only language constructs are visible -- either wrapper-library calls or custom syntax.  From the application-programmer point of view, even an embedded parallelism construct looks like a function call, albeit the data-structure of the virtual-processor animating the code has to be passed as a parameter to the wrapper-lib call.
 
- 
-
 
 \subsection{Interface from top to middle}
 
@@ -221,15 +219,9 @@
 
 \subsection{Interface from middle to bottom}
 
-
-
-
 VMS's plugin API is the interface between the runtime and the bottom abstraction-implementation. The API has calls to register  language-supplied runtime functions with the bottom abstraction, as well as support services. 
 
 
-
- 
-
 Reduction of the number of runtimes is accomplished this way. Hardware targets with similar structure present the same interface, requiring only one runtime. 
 
 Only structural elements that affect assignment choices are exposed in the API.  For example, memory hierarchy is exposed as a VMS-defined data-structure made available to the sched-assign function. The details in the data convey the connectivity, communication, and sizes, which the assigner may use to optimize choices.  
@@ -244,14 +236,13 @@
 
 The code consists of two loops: the innermost is a single task, while the outer repeats that task a number of times.  The inner does throw-away work entirely within registers, where the number of iterations sets the amount of work in the task.  After the inner completes, a synchronization is performed, which pairs each task to a sync operation.  The outer then repeats the sequence of task-then-sync a large number of times to gain statistical accuracy and dominate any other sources of overhead.
 
-Two versions of the code were written: one that used pthread, a second that used a VMS-implemented equivalent called Vthread.  Both versions have the same semantics, differing only in the implementation of scheduling triggered by the  construct.  Hence, any difference in execution time is due to the difference in scheduling overhead.  Pthread uses the pthread library's scheduling which layers over the Linux kernel's implementation.  Vthread uses a VMS plugin that layers over the VMS system's implementation of the tie-point guarantee.
-
+Two versions of the code were written: one that used pthread, a second that used a VMS-implemented equivalent called Vthread.  Both have the same semantics, differing only in the implementation of scheduling triggered by the  construct.  Hence, any difference in execution time is due to the difference in scheduling overhead.   
 
 %%%%%%%%%%%%%%%%%%%%%%%
 \section{Results}
 The new experimental results given in this paper focus on the overhead of the runtime, with the goal of showing that a language based on VMS enjoys low overhead compared to standard pthreads.  We illustrate the amount of overhead by plotting a curve whose shape is determined by the overhead.
 
-The idea of the curve is to compare total CPU time to just the time spent doing work.  The difference between them is the overhead of scheduling, including synchronization construct overhead, which consists of: switching from application to scheduler; updating the sync-construct state; choosing a new thread to schedule; and deciding on which core to re-animate that thread.
+The curve  compares total CPU time to just work time. The difference is the overhead of scheduling,  which consists of: switching from application to scheduler; updating the sync-construct state; choosing a new thread to schedule; and deciding on which core to re-animate it.
   
 The ratio of total CPU time to work time gets larger as the overhead increases, raising overhead's percent of the total.  When the ratio is exactly 2, the work time exactly equals the overhead.  Larger ratio indicates overhead dominates, smaller indicates work dominates.
 
@@ -265,7 +256,7 @@
 \begin{figure}[ht!]
  \includegraphics[width=2.3in, angle = -90]{plots_exec_vs_task_size/cray1_pthread_vthread_8_32_128_512thds__o30000__perfCtrs.eps}
  \caption
- {$\frac{ExecutionTime} {WorkTime}$  vs  $TaskTime$ on the 1x2 machine. It shows results for Vthread and pthread on the same axes, for 8 through 512 threads. The curves for Vthread are in a cluster, all appearing to be the bottom-most curve, while the pthread curves for 8, 32, and 128 are the three above it. The results for pthread with 512 threads land outside the plot.
+ {$\frac{ExecutionTime} {WorkTime}$  vs  $TaskTime$ on the 1x2 machine. It shows results for Vthread and pthread on the same axes, for 8 through 512 threads. The Vthread curves cluster, appearing as the bottom-most, while the pthread curves for 8, 32, and 128 are  above it. The results for pthread with 512 threads land outside the plot.
   }
 \label{figCray1Results}
 \end{figure}
@@ -315,12 +306,9 @@
  
  
 \subsection{Implementation Time Results}
-As seen in a previous paper on VMS\cite{}, it makes runtime implementation quick and easy.  The results are re-printed here to support the claim that VMS meets the requirement of reducing runtime implementation effort. 
+As seen in a previous paper on VMS\cite{VMSLCPC}, it makes runtime implementation quick and easy.  The results are re-printed in Table \ref{tabPersonDaysLang} to support the claim VMS meets the requirement of reducing runtime implementation effort. 
 
-From previous experience and informal discussions with others, equivalently low-overhead tuned runtimes created the traditional way would take several months. Similar time is also expected to learn the code of a pre-existing multi-threaded highly tuned runtime, then modify, debug and re-tune it.
-
-Implementation time is reduced by the uniform nature of VMS-based runtimes, freedom from details hidden by the VMS interface, the helper facilities VMS provides, VMS's debugging facilities, and freedom from multi-threading issues due to VMS's tie-point based ordering guarantee.  When combined, they lead to the fast implementation times seen in Table \ref{tabPersonDaysLang}.  
-
+From previous experience and informal discussions with others, equivalently low-overhead tuned runtimes would take several months. Similar time is also expected to learn the code of a pre-existing multi-threaded highly tuned runtime, then modify, debug and re-tune it.  
 
 \begin{table}[ht!]
 \caption
@@ -344,99 +332,15 @@
 
 
 %%%%%%%%%%%%%%%%%%%%%%
-\section{Future Work}
-To further explore the simplification and effort-reduction provided by the VMS abstraction, a semester long project course is being given for undergraduates. In the class, pairs of students design and implement a domain-specific parallel language built upon VMS and embedded into C.  They are asked to track the time spent on each phase of design and implementation of their language.
-
-
-%%%%%%%%%%%%%%%%%%%%%%%
 \section{Conclusion}
-
-
-The Need: background on portability stack -- the end-goal sought, the fundamentals involved in any solution to provide it, how proposed stack from last year is updated to accord with those fundamentals in achieving end-goal.  The elements of the stack.  What function/role each element serves.
-
-Describe details of bottom of software stack
-
-what need in bottom, to support eco-system\cite{} 
- 
- 
-Expect domain-specific languages -- these embed new behaviors into base language.  Different from library because cannot understand the behavior of the call based on the base language alone. The runtime system provides behavior beyond the base language.  This approach makes for quick  creation of languages specialized to narrow domains.
+We showed that using VMS as the bottom hardware abstraction in a software stack pulls low-level tuning out of the runtimes, reduces the number of runtime implementations, and encourages reuse of scheduler assignment code across languages.
 
 
 %%%%%%%%%%%%%%%%%%%%%%%%
-\section{How VMS Fulfills the Abstraction Requirements}
 
-\subsection{Why not pthreads?} 
 
-At first, it seems that interfaces for building runtimes already exist: pthreads, or MPI, or even OpenCL. They all hide low-level hardware details, while allowing tuning application performance critical details. However, upon closer inspection it becomes clear that these all fail to separate concerns in the runtime,  don't enforce uniform patterns, don't hide concurrency, don't supply common runtime services, and don't encourage reuse.
+\bibliography{../helpers/bib_for_papers}
 
-  It may be possible to use these interfaces to implement a higher-level interface that accomplishes the effort-reduction needed.  However, such an interface would end up looking much like VMS, and when compared to the simplicity of VMS, which has only a few hundred lines, and compared to the low overhead measured in Section 6, and given that the extra layers interfere with performance tuning, such an alternative may not be worth the effort. 
-
- 
-
-\subsection{VMS's influence on the stack}
-
-VMS affects the interfaces between layers of the stack. At the top, VMS determines the way parallel constructs are embedded into base languages, and how custom-syntax languages generate their runtime-interactions.  Between the top and middle, VMS defines the interface for the language/toolchain layer to talk to the runtime layer. Within the middle layer, VMS defines two standard function prototypes, and a runtime consists of implementations of these two functions.  Between middle and bottom, VMS defines a number of services that runtimes in the middle can call, and also defines the interaction between the abstraction-implementation and the two runtime functions.
-
-
-\subsection{VMS as a runtime simplifier}
-
-VMS fulfills the role of simplifying runtime construction in three ways: 1) it removes low-level hardware details from the runtime, especially those related to performance of the runtime itself  2) concurrency of the runtime itself is handled by VMS, so the language-specific portion uses sequential thinking 3) VMS provides the most common services a runtime needs, such as creation of new tasks, distributed malloc, and so on.
-
-Handling the runtime's internal concurrency appears to be the most significant simplifier, closely followed by encapsulating low-level performance details.
-
-When asking those who implemented their runtimes using hardware locks, lock-free constructs, or pthreads, the bulk of their time went to debugging subtle concurrency issues, and attempting to lower the overhead of internal synchronizations by hand-tweaking on hardware-specific issues.  Informally, accounts range from one and a half to six months to implement the runtime for a new language, depending mostly on amount of performance tuning.
-
-Similar time has gone into the creation and performance tuning of VMS.  On each target machine, details of the atomic instructions, coherency protocol, and communication times force intense low-level tuning of the VMS code.
-
-However, when implementing the runtime for a new language, by using VMS, such details are hidden, resulting in implementation times measured in days.  More significantly, a novel parallel construct can be added in mere hours.  That improvement is due to the language-specific portion being decoupled from the low-level hardware and concurrency details.
-
-
-
-\subsection{VMS as reducer of number of runtimes}
-
-Pulling low-level details underneath the abstraction has a second benefit. For all hardware targets with similar application-performance details, the same runtime achieves high runtime-performance.  Hence, only one runtime per language is needed for all those targets.  So, pulling details out of the runtime and placing them beneath the abstraction has not only simplified runtime implementation, but also reduced the number of runtime implementations.
-
-\subsection{VMS as a runtime uniform-izer}
-
-In the bigger picture, when a new 
-
-\subsection{VMS as a reuse encourager}
-
-The language-specific parts of the runtime consist of handling constraints on scheduling work, and choosing where and when to assign the work to animators (IE, where and when to execute).
-
-
-%%%%%%%%%%%%%%%%%%%%%%%%%%
-\section{Availability}
-
-VMS is free software, available from the homepage at \url{http://www.virtualizedmasterslave.org}
-
-
-\begin{thebibliography}{99}
-
-\bibitem{beazley} D.~M.~Beazley and P.~S.~Lomdahl, 
-\emph{Message-Passing Multi-Cell Molecular Dynamics on the Connection
-Machine 5}, Parall.~Comp.~ 20 (1994) p. 173-195.
-
-\bibitem{CitePetName} A.~N.~Author and A.~N.~Other, 
-\emph{Title of Riveting Article}, JournalName VolNum (Year) p. Start-End
-
-\bibitem{embed} Embedded Tk, \url{ftp://ftp.vnet.net/pub/users/drh/ET.html}
-
-\bibitem{expect} Don Libes, \emph{Exploring Expect}, O'Reilly \& Associates, Inc. (1995).
-
-\bibitem{heidrich} Wolfgang Heidrich and Philipp Slusallek, \emph{
-Automatic Generation of Tcl Bindings for C and C++ Libraries.},
-USENIX 3rd Annual Tcl/Tk Workshop (1995).
-
-\bibitem{ousterhout} John K. Ousterhout, \emph{Tcl and the Tk Toolkit}, Addison-Wesley Publishers (1994).
-
-\bibitem{perl5} Perl5 Programmers reference,
-\url{http://www.metronet.com/perlinfo/doc}, (1996).
-
-\bibitem{otcl} D. Wetherall, C. J. Lindblad, ``Extending Tcl for
-Dynamic Object-Oriented Programming'', Proceedings of the USENIX 3rd Annual Tcl/Tk Workshop (1995).
-
-\end{thebibliography}
 
 \end{document}
 
diff -r e455dad92745 -r bc4dd419ed1a 0__Papers/VMS/VMS__Foundation_Paper/HotPar_2012/latex/Paper_Design_2.txt
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/0__Papers/VMS/VMS__Foundation_Paper/HotPar_2012/latex/Paper_Design_2.txt	Thu Feb 02 12:20:28 2012 -0800
@@ -0,0 +1,32 @@
+
+======
+
+Details of VMS interface, details of its impl on multi-core, details of differences on different machines.
+
+wrapper-lib calls VMS-supplied primitive that suspends the virtual-processor calling the lib, and sends a request to VMS.  VMS calls lang-supplied plugin to handle requests -- this is the part of the scheduler that handles constraints -- it determines which virt-processors must remain suspended, and which are free to be re-animated.
+
+The language is implemented as either a collection of wrapper-lib calls embedded into the base language, or as custom syntax that uses uses the VMS-supplied primitive to suspend virtual processors and send requests to VMS.
+
+
+VMS is invisible to the application, only language constructs are visible.  From the application-programmer point of view, the embedded version looks like a function call, albeit the data-struc of the virtual-processor animating the code has to be passed as a parameter to the wrapper-lib call.
+
+Hence, VMS is invisible to the application, only language constructs are visible.  
+
+The wrapper-lib call is standard library code that is loaded along with the application executable.
+
+However, VMS primitives may be hardware-implemented, or loaded as OS modules, or dynamic or static libraries. Rhey are naturally custom instructions, but may be emulated by software.
+
+The interface between application-executable and language-runtime is the VMS-primitive that sends a request to VMS.  The language-runtime receives the request under control of VMS, which calls a language-supplied request-handling function and passes the request as a parameter.  This passive behavior of the request handler leaves control-flow inside VMS, which is part of hiding concurrency from the language-runtime implementation.
+
+The interface between the runtime and VMS is VMS's plugin API.  The runtime is implemented as two functions, whose pointers are handed to VMS.  VMS then controls the flow of execution.  When a request is ready for the runtime, VMS cIalls the request-handler function, and when a spot on hardware is free for work, VMS calls the scheduler-assign function.  Hence, the language implements its runtime as two isolated functions.  By keeping control-flow inside VMS, the language-specific portion of the runtiem is simplified.
+
+This structure is also the reason VMS encourages reuse of scheduler code. The VMS API separates out control flow from scheduling, so scheduling code is isolated, with well-defined interfaces.  Scheduling is then further sub-divided into modules: constraint-management (IE enforcing dependencies); and choosing physical location to place work. Each has its own well-defined interface, and they communicate to each other via VMS-managed shared state.
+
+The greatest application performance impact due to the scheduler is communication it causes.
+
+, management of the memory hierarchy, and the match between work-characteristics and hardware-characteristics (IE, assigning to accelerator vs CPU).  Hence, significant work goes into implementing strategies and mechanisms for finding the best assignment-choices. Such implementations are only loosely coupled to language, through the shared state by which the request-handler informs the assigner of what work is ready to be animated.
+   
+Hence, it is straight-forward to reuse the code that assigns work to physical locations.  The only language-specific influence on the assigner is the shared constraint-state.
+
+ 
+
diff -r e455dad92745 -r bc4dd419ed1a 0__Papers/VMS/VMS__Foundation_Paper/LCPC_2011_Photo_Ready/latex/June_2011__Thread_replacement__Photo_Ready__LNCS.tex.Backup-20110921-022757
--- a/0__Papers/VMS/VMS__Foundation_Paper/LCPC_2011_Photo_Ready/latex/June_2011__Thread_replacement__Photo_Ready__LNCS.tex.Backup-20110921-022757	Tue Jan 31 18:03:47 2012 -0800
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-% does not allow \baselineskip to stretch. Authors submitting work to the
-% IEEE should note that IEEE rarely uses double column equations and
-% that authors should try to avoid such use. Do not be tempted to use the
-% cuted.sty or midfloat.sty packages (also by Sigitas Tolusis) as IEEE does
-% not format its papers in such ways.
-
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-% *** PDF, URL AND HYPERLINK PACKAGES ***
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-%\usepackage{url}
-% url.sty was written by Donald Arseneau. It provides better support for
-% handling and breaking URLs. url.sty is already installed on most LaTeX
-% systems. The latest version can be obtained at:
-% http://www.ctan.org/tex-archive/macros/latex/contrib/misc/
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-% *** Do not use packages that alter fonts (such as pslatex).         ***
-% There should be no need to do such things with IEEEtran.cls V1.6 and later.
-% (Unless specifically asked to do so by the journal or conference you plan
-% to submit to, of course. )
-
-
-% correct bad hyphenation here
-\hyphenation{op-tical net-works semi-conduc-tor}
-
-
-\begin{document}
-
-\bibliographystyle{plain}
-%
-
-\title{A Mutable Hardware Abstraction to Replace Threads}
-
-\author{Sean Halle\inst{1,2,3} \and Albert Cohen\inst{1}}
-\institute{INRIA and \'Ecole Normale Sup\'erieure, France
-  \and
-  University of California at Santa Cruz, USA
-  \and
-  Technical University Berlin}
-
-\maketitle             
-%
-
-\begin{abstract}
-  We propose an abstraction to alleviate the difficulty of programming
-  with threads. This abstraction is not directly usable by application
-  programmers.  Instead, application-visible behavior is defined
-  through a semantical plugin, and invoked via a language or library
-  that uses the plugin.  The main benefit is that parallel language
-  runtimes become simpler to implement, because they use sequential
-  algorithms for the parallel semantics. This is possible because the
-  abstraction makes available a virtual time in which events in
-  different program time-lines are sequentialized.  The parallel
-  semantics relate events in different time-lines via relating the
-  sequentialized versions within the virtual time-line.
-
-  We have implemented the abstraction in user-space and demonstrate
-  its low overhead and quickness to implement a runtime on three sets
-  of parallelism constructs: rendez-vous style \texttt{send} and
-  \texttt{receive}; Cilk style \texttt{spawn} and \texttt{sync}, which
-  have similar performance to Cilk 5.4; and \texttt{mutex} and
-  \texttt{condition variable} constructs from pthreads, which have 80x
-  lower overhead than Linux thread operations.  Development time
-  averaged around two days per set, versus an expected duration  of weeks to modify a thread-based runtime system.
-\end{abstract}
-
-\section{Motivation}
-
-Thread parallelism constructs have been well documented to be
-difficult to program with. They directly expose low-level concurrency
-to the programmer. Arbitrary non-deterministic behavior and deadlocks
-can arise from improperly synchronized code. Efficient execution
-requires non-blocking algorithms whose correctness require deep
-understanding of weakly consistent memory models. In addition, the
-operating system abstraction for threads comes with a very high
-context-switching and synchronization overhead.
-
-%% AC. The following is wrong.
-%\paragraph{\bf Problems with threads: } Thread parallelism constructs have been well documented to be difficult to program with. In addition, threads are problematic when one has multiple physical cores because the thread abstraction hides the hardware, disabling control over placement of tasks.  High performance requires such control. Hence, not only are threads  difficult to use directly in applications, but they prevent easier parallelism constructs from being built on top of them that have high performance.
-
-%\paragraph{\bf Partial solution: } To deal with this, in practice, a language's runtime turns off
-
-\paragraph*{A partial solution.}
-
-To deal with the last problem, a parallel language's runtime turns off
-operating system threads by pinning one to each physical core.  This
-way, the custom runtime is assured that the software thread is
-one-to-one with a physical core. It then implements a user-level
-thread package that lets it control which OS thread a computational
-task is assigned to. Finally, the runtime then implements the
-language's parallel semantics in terms of those user threads.
-
-The user-level threading approach addresses the system overhead issue,
-but it still hides important events such as input-output or
-node-to-node communications in a cluster.
-%% AC. Irrelevant for a parallelism-centric paper
-%software faults, and other hardware events
-Scalable runtimes need to coordinate task assignment
-to cores with application access of input and output, memory
-allocation over non-uniform cache and memory hierarchies, offloading
-to hardware accelerators, power management, and inter-node
-communication in a cluster.  The user-level threading approach is hampered in addressing these needs, and
-further makes the parallel runtime implementation cumbersome, error-prone and
-complex, because it is still written in terms of threads.
-
-
-Ideally, the OS would be in terms of a mutable hardware abstraction, and export mutations as new behavior.  We define a mutable hardware abstraction to be an interface to hardware-level behaviors that are normally inside the OS or below it. Examples include communication between cores, allotting time-slots to applications, and establishing ordering of events among cores (which is what atomic memory operations and equivalent patterns of instructions do).  The kernel itself would be implemented in terms of such an abstraction, and would accept mutations the same way it accepts device-drivers. It would then export the mutated behaviors for the language to trigger.
-
-A language  runtime would be in the form of a mutation. Being inside the OS, it has secure access to kernel-only hardware mechanisms. It could directly negotiate with the kernel to manage physical resources, in a low-overhead way.  The arrangement enables the runtime to control which task is assigned to which processing element at what time.  Both high performance and low-energy depend on this for implementing data affinity techniques. For example, the runtime could track data within the memory hierarchy and assign tasks to locations close to their consumed data.
-
-% \paragraph{\bf Support for portability: } This separation between
-% application executable and language runtime also supports
-% portability. It packages the language-specific scheduler into a
-% separate machine-specific module that is separately installed. The
-% scheduler is thus optimized for the combination of language with
-% hardware. This isn't a full solution to portability but it is a needed
-% precursor.
-
-% An interesting portability technique enabled by a separate
-% language-plus-hardware specific runtime is tracking which cores are
-% likely to already have data in the cache which a new task requires as
-% input. It could place tasks where the input data is likely to reside,
-% reducing communication to increase performance and power efficiency.
-
-\paragraph*{Contribution.}
-
-We show in this paper the definition and implementation of such a
-mutable hardware abstraction, albeit at user-level rather than in
-the kernel.  The abstraction lets a language's runtime be implemented as
-a mutation, which we call a plugin.  The plugin implements parallelism constructs and assignment of tasks to cores.
-
-We focus in this introductory paper on the definition of the
-abstraction and its support for parallelism constructs, postponing
-exploration of assignment of tasks onto cores and other performance
-optimizations to following papers. This paper defines multiple time-lines in a program, and a virtual timeline that globally orders events among them. It demonstrates three sets of parallelism constructs: synchronous \texttt{send}-\texttt{receive}
-motivated by process calculi; \texttt{spawn} and \texttt{sync} from
-Cilk {\cite{Fri98,CILKHome}}; and \texttt{mutex} and \texttt{condition
-  variable} from pthreads.  The assignment policy we implemented with
-them is simply first-come first-served.
-
-We call the abstraction Virtualized Master-Slave, or VMS. It
-exports facilities to create virtual processors and control how their timelines relate to each other, and relate to physical time. It also exports facilities to suspend a virtual processor and for an executable to interact with the plugin. The plugin embodies most of a language's runtime. A wrapper-library or keyword is what appears in application code, and is what triggers the runtime.
-
-\paragraph*{Organization of paper.}
-
-Section~\ref{secAbsModel} provide the original concepts and
-definitions of VMS. Section~\ref{secInternal} focuses on the
-implementation, describing the elements and how they interact, then
-relating them back to the theoretical definition.
-Section~\ref{secApp} takes the point of view of the application code,
-studying the usage and implementation of parallel language constructs
-as a VMS plugin. To wrap up, measurements of effectiveness appear in
-Section~\ref{secResults} and conclusions in
-Section~\ref{secConclusion}.
-
-\section{Background and Related Work}
-
-User-level thread packages and most parallel language runtimes have to
-side-step OS threads, by pinning one to each core, which effectively
-gives the user-level package control over the core. Our VMS
-implementation also does this. We are not claiming in this paper to
-have the OS level implementation of VMS that is possible -- but just
-the user-space version.
-
-\paragraph*{Related work.}
-
-The most primitive methods for establishing ordering among cores or distributed processors are atomic instructions and clock-synchronization techniques \cite{Lamport78,Christian89}.
-
-Meanwhile, the most closely related work is Scheduler Activations
-\cite{SchedActivations}, which also allows modifying concurrency
-constructs and controlling assignment of virtual processors onto
-cores. However it has no virtual time to guarantee globally consistent
-sequentialization, and no interface for plugins.
-
-BOM \cite{BOMinManticore}, which is used in Manticore to express
-scheduling policies and synchronization, also bears resemblances to
-VMS, but at a higher level of abstraction. BOM is a functional
-language, rather than a primitive abstraction meant to sit at the
-hardware-software boundary as VMS is.
-
-Coroutines is a high-performance means of switching between
-tasks. Coroutine scheduling and stack handling techniques were well
-suited to the user-space implementation of VMS.
-
-Other related work either provides an abstraction of the thread model,
-or is a full language with specific parallelism constructs. As a
-protypic example of user-level threads, Cilk {\cite{Fri98,CILKHome}}
-provides a simplified abstraction with an efficient scheduling and
-load balancing algorithm, but limited to fork-join concurrency. OpenMP
-{\cite{OpenMPHome}} is a typical example of a parallel extension of
-sequential languages; it allows creating tasks and controlling their
-execution order. We claim that both Cilk and OpenMP, as well as most
-thread abstractions or parallel languages may be implemented via
-plugins to VMS, with similar performance.
-
-VMS is unique in that it doesn't impose its own concurrency semantics as a programming model, but rather takes preferred ones as plugins. This
-makes it only a \emph{support} mechanism to
-implement language runtimes -- VMS is hidden from the application, underneath the language. Parallelism constructs may be implemented
-as VMS plugins, easily, quickly, and with high performance as
-indicated in Section~\ref{secResults}.
-
-This work presents a first incarnation  of VMS. We plan
-to explore the embedding into VMS of a variety of parallel languages,
-with a special interest for coordination languages
-\cite{Gelernter85Linda,CnCInHotPar,CnCHome}. We will also explore
-VMS's compatibility with different concurrent semantics
-\cite{Kah74,hoare78,milner99,Hewitt10,Actors97}. One particularly
-important application would be to use VMS to facilitate the design and
-implementation of the emerging hybrid programming models, such as
-MPI+OpenMP, or OpenMP+OpenCL \cite{Car10,OpenCLHome}.
-
-
-\section{Abstract Definition of VMS}
-\label{secAbsModel}
-
-We start with an intuitive overview, then precise the definitions and
-properties in the following sub-sections.
-
-\paragraph*{Definitions:}
-
-1) We want to avoid the confusion associated with the various
-interpretations for the terms ``thread'' and ``task'' so will use
-the term \emph{Virtual Processor} (VP), which we define as state in
-combination with the ability to animate code or an additional level of
-virtual processors. The state consists of a program counter, a stack
-with its contents, a pointer to top of stack, and a pointer to the
-current stack frame. 2) A \emph{physical processor}   executes
-a sequential stream of instructions.
-3) A program-timeline is the sequence of instructions animated by a
-Slave VP, which is in turn animated by a physical processor.
-
-
-\paragraph*{Intuitive Overview.}
-
-VMS can be understood via an analogy with atomic instructions, such as Compare and Swap (CAS). These are used to establish an ordering among the timelines of cores. They consist of two parts: 1) the semantics of what is done to the memory location, 2) a mechanism that establishes an ordering among the cores.  For CAS, the semantics are: ``compare value in this register to value at the address, and if same, then put value in second register into the address.''  Multiple kinds of atomic instructions share the same order-establishing mechanism, they simply provide different semantics as a front-end.
-
- VMS can be viewed as virtualizing the order-establishing mechanism. It allows the semantics to be plugged-in to it. This breaks concurrency constructs into two parts: the VMS mechanism, which establishes an ordering between events in different timelines; and the plugin, which supplies  the semantics.
-
- Below the interface, hardware mechanisms are employed to order specific points in one physical processor's timeline relative to specific points in another's timeline.    Above the interface, a plugin  provides the semantics that an application uses to invoke creation of the ordering. 
-
-Together,  VMS plus the plugin form a parallelism construct, by which an application controls how the time-lines of its virtual processors relate. Such constructs also guarantee relations of VP time-lines to hardware events.
-
-As an example, consider a program where one VP writes into a data structure then calls a \texttt{send} construct. Meanwhile, a
-different VP calls the \texttt{receive} construct then reads
-the data structure. The semantics of the \texttt{send} and \texttt{receive} constructs are that all data
-written before the \texttt{send} is readable in the other time-line
-after the \texttt{receive}.
- To implement these constructs, VMS provides the mechanism to enforce the ordering, and to include the writes and reads in that ordering.  The plugin directs that mechanism to order the \texttt{send} event before the \texttt{receive} event.
-%% AC. Too early.
-% VMS provides a primitive guarantee that
-% plugin code builds upon to provide such higher-level guarantees. The
-% primitive guarantee is defined in Section~\ref{scTime}, after the
-% necessary vocabulary is established.
-
-\paragraph{What the VMS interface provides:} The interface provides primitive operations
-to create and suspend VPs; a way for plugins to control when and where
-each VP is (re)started; a way for application code to send requests to the plugin; and a way to order a specific point in one VP time-line relative to a specific point in another VP time-line. All implementations of the VMS interface provide these, whether  it is on shared memory or distributed, with
-strong memory consistency or weak.
-
-\paragraph*{Specification in three parts.}
-
-We specify the observable behavior of a VMS system \emph{with plugins present}.  Hence,
-the specified behaviors remain valid with any parallelism construct
-implementable with VMS.  First we give the specification of a computation system that VMS is compatible with; then specify a notion of time and the key VMS guarantee; and lastly specify
-virtual processor scheduling states and transitions between them.
-
-%% AC. Too early, Master has not been defined. I renamed VMS-core into
-%% VMS afterwards, finding no ambiguity.
-% The Master mentioned in the definition is an abstract entity, with a
-% plugin present. In practice, this Master entity is implemented as part
-% of a core VMS, and plugins later added. This VMS-core is the hardware
-% abstraction. It hides the physical hardware behind an interface that
-% creates virtual processors and enforces well-defined time-behavior.
-
-\subsection{The Specifications for a VMS-compatible Computation System}
-
-\begin{itemize}
-\item An application creates multiple VPs, which are Slaves, each with an
-  independent time-line.
-\item A schedule of Slaves is generated by a Master entity, from
-  within a hidden time-line(s).
-\item A schedule is the  set of physical locations and time-points at which Slaves are
-  (re)animated.
-\item All semantic parallelism behavior is invoked by Slaves communicating
-  with the Master.
-\item A Slave communicates with the Master by using a VMS primitive,
-  which suspends  the Slave.
-\end{itemize}
-
-\paragraph{Where we define:}
- Semantic Parallelism Behavior is the actions taken by a parallelism construct, which establishes an ordering among events in different Slave timelines.
-
-
-\paragraph{Discussion:}  The key point is that
-\emph{scheduling is separated from the application code}. This is enforced by the schedule being generated in a time-line hidden from the application. The rest of the requirements are consequences of that separation.
-
-The Master entity appears as a single entity, to the slaves. However it may
-be implemented with multiple (hidden) timelines.  This is the approach taken in our initial implementation, which has several Master VPs hidden inside the VMS
-implementation.
-
- 
-
-
-%% AC. Calling memory a processing element only adds confusion.
-% {\bf Definitions:\ }VMS is intended only for hardware systems that
-% consist of processing elements connected by communication.  We define
-% a memory-space to be a processing element, albeit without the ability
-% to transform data.
-
-
-\subsection{The Time-Related Specifications of VMS}
-\label{secTime}
-
-To prepare for the time-related specifications, we give an advance peek of the following section, 3.3. There, Slave VPs are specified to have three scheduling states: Animated, Blocked, and Ready.  When a  parallelism construct starts execution, the Slave  transitions from Animated to Blocked. When it ends execution, the Slave transitions from Blocked to Ready.    VMS provides a way to control the order  of these state-transitions, which is equivalent to controlling the order of the parallelism-constructs.  Controlling the state transitions is how the ordering among constructs in different timelines  is established. 
-   
-With that background, here are time-related specifications for VMS: \begin{itemize}
-\item VMS provides a Virtual timeline that globally orders changes of scheduling state  of Slave VPs.
-\item Ordering is created among construct-invocations by controlling the order of Blocked to Ready transitions in the Virtual timeline.
-\item 
-Causally tied construct-invocations are  tied-together inside the Master. \item VMS enforces ordering of \textit{observations} of physical events  in Slave timelines to be consistent with the Virtual time ordering.
-\item Virtual time defines only ordering, but not spans, nor widths.
-\end{itemize}
-
-\paragraph{Discussion:} 
-Most importantly here, Virtual time defines a global ordering among Slave state-transitions. To make this useful for parallelism,  VMS must be implemented so that observations of physical events, like reads and writes to shared memory, are consistent with that ordering. 
-
-The Virtual timeline plays the same role as the mechanism added to memory systems to support atomic instructions. All atomic instructions require hardware that establishes an ordering among the timelines of physical cores. That hardware sequentializes execution of atomic memory accesses to the same address. VMS virtualizes this mechanism.  It provides the same ordering function.
-
-An important point is that the Virtual timeline is generated inside the Master. When a Slave uses the VMS primitive to send a parallelism-construct request, it suspends.  However, that Slave doesn't actually transition state from Animated to Blocked until the Master \textit{acknowledges} the suspension.  It is the  acknowledgement that adds the Slave transition into the Virtual timeline.
-
-The essential value of VMS is using it to control the order of observing events. It has to be able to causally link the execution of a parallelism construct in one timeline to the execution of a construct in a different timeline. Establishing such a causal link is called \textit{tying together} two construct executions.
- It is specific executions from different timelines that are causally linked with such a tie.
-\paragraph*{The key VMS guarantee:}
-
-the order of observing physical events is consistent with the order of tied together parallelism constructs. 
-
-To explain this, take as given:  two Slaves both execute parallelism constructs, those are tied together by the Master, establishing a causal ordering from one to the other. So, one construct is the \textit{before}-construct, the other is the \textit{after}-construct. Now, the guarantee means that any events triggered before the before-construct, in its timeline,   are guaranteed to be detected in the other timeline as also preceding the after-construct.  In addition, events triggered after the after-construct are guaranteed not visible before the before-construct in its timeline. This two-part guarantee is the result of the above specifications of VMS's time-related behavior.
-
-
-
- 
-\paragraph*{Definitions:}
-
-Some more definitions, to prepare for the next explanation. 1) An \textit{ordering-point} exists in a Slave VP's timeline as a zero-width event that can be tied to ordering points in other timelines. It is initiated by a Slave VP executing the suspend
-primitive, and ended by the Master transitioning the Slave back to Animated. 2) A trace-segment is a portion of a Slave VP's stream of instructions bounded by ordering-points. 
-
-Hence, the timeline of a Slave is a sequence of trace-segments. Each
-trace-segment is animated by a single physical processor, but not
-necessarily the same  as animated the Slave's other trace segments.
-
-  
-
-
-\begin{figure}[ht]
- \includegraphics[width=3.5in]{../figures/Time_in_VMS_2.eps}
- \caption
- {Time Behaviors:  \ Shows Ordering Point 1.1 being tied to Ordering Point 2.1. As a result, VMS guarantees that events triggered in Trace Segment 1.1 are seen as having taken place in the past in Trace Segment 2.2.  Also shows that there is no common tied ordering point between segments 1.2 and 2.2, so VMS provides no guarantees about what order segment 2.2 sees events triggered in segment 1.2.
-  }
-\label{figTimeMapping}
-\end{figure}
-
-\paragraph*{Relating time-lines to each other.}
-
-Figure \ref{figTimeMapping} shows two ordering points being tied together. A trace segment starts, at the same time an ordering-point ends, by its Slave transitioning to Animated.  Because the transition to Animated exists as a point in Virtual time, the start of a trace-segment has a well-defined position within Virtual time. Likewise, a trace-segment is ended by its Slave executing the suspend primitive of VMS.  Although this does not have a well-defined point in Virtual time, every execution of suspend is acknowledged by the Master, which transitions the Slave to Blocked.  That transition does have a well-defined position in Virtual time. Hence, the end of every trace-segment is associated with a well-defined position in Virtual time.
-
-As a result, trace segments can be ordered relative to each other, by checking their start and end points in Virtual time. If they have no overlap in virtual time then they have a total ordering. However, if any portion of them overlaps in Virtual time, then they are considered concurrent trace-segments, and their Slaves are considered to be executing in parallel between those points of Virtual time.  
-
-Note that this is conservative because it doesn't take into account the physical wait time between a Slave suspending and the Master acknowledging. The Slave may stop executing at a physical time-point that would map onto an earlier point in Virtual time. In some cases, ending the Slave's trace-segment at the earlier point would eliminate the overlap with a particular other trace-segment.  But VMS's set of specifications doesn't allow such mapping of suspend-execution onto Virtual time (for implementation-related reasons, which require downloading the code and gaining experience with it, to establish a common language, for an explanation to be understood).
-
-
-
-A  subtlety is that events triggered
-before one tied ordering-point, {\em{might}} be visible in the other timeline before the other tied ordering-point.  In the figure, segment 2.1 might be able to see events from segment 1.1 if it looked.  The VMS guarantee doesn't cover overlapped trace-segments. Physical events triggered before are only guaranteed visible
-{\em{after}} the tie point, and events after are only guaranteed
-{\em{not}} visible {\em{before}} the tie point.
-
-We call this bounded non-determinism, because events within overlapped trace-segments have non-deterministic ordering, but the region of non-determinism can be bounded by tied ordering-points. This allows a program to specify non-determinism, but control the region of non-deterministic behavior.  For example, a reduction construct could be created that non-deterministically assigns portions of the reduction work to overlapped Slave segments. It would tie together ordering points from all the Slaves that mark the end of reduction.  Hence, the outcome is deterministic, but the path to get there is not.
-
-\paragraph*{Sequential algorithms for parallel constructs.}
-The globally-consistent sequential order in Virtual time enables one
-of VMS's main benefits: sequential algorithms for parallel constructs.
-An implementation to
-tie ordering points together equals an implementation of parallel constructs. A plugin has an ordering of state transitions available, and chooses from those. Sequential algorithms rely on an ordering existing, while concurrent algorithms must include operations that establish an ordering.  Plugins have Virtual time ordering available, so they can use sequential algorithms.  
-\subsection{Specification of Scheduling State}
-
-Scheduling state is used in VMS to organize internal activity, for
-enforcing the guarantees.
-
-\begin{itemize}
-\item VPs have three scheduling states: {\em{Animated}},
-  {\em{Blocked}}, {\em{Ready}}; see Figure~\ref{figStates}.
-\item VPs in Animated are {\em{allowed}} to advance Program time with
-  (core-local) physical time.
-\item VPs in Blocked and Ready do not advance their Program time.
-\item Animated has two physical states: {\em{Progressing}} and
-  {\em{Stalled}}.
-\item VPs in Progressing advance Program time with (core-local)
-  physical time, those in Stalled do not (allowing non-semantic
-  suspend for hardware interrupts).
-\item Scheduling states are defined in Virtual time only.
-\item Progressing and Stalled are defined in (core-local) physical
-  time only; the distinction is invisible in Virtual time.
-\end{itemize}
-
-\begin{figure}[h!tb]
-\begin{minipage}{.55\textwidth}
-  \includegraphics[width=\textwidth]{../figures/Scheduling_states_2.eps}
-  \caption{Scheduling states of a slave VP in the VMS model. Animated, Blocked, and Ready are only defined in Virtual Time and only visible in the Master.  Progressing and Stalled are only visible in physical-processor local time, not visible in Virtual time.}
-  \label{figStates}
-\end{minipage}
-\hfill
-\begin{minipage}{.43\textwidth}
-  \includegraphics[width=\textwidth]{../figures/VMS-core__plugins.eps}
-  \caption
- {
-  The Master, split into a generic core and a language-specific plugin.
-  The core encapsulates the hardware and remains the same across applications.
-  The plugin implements the semantics of the parallelism-constructs.
- }
- \label{figMasterSplit}
-\end{minipage}
-\end{figure}
-
-
-Some important points: (1) only VPs Animated can trigger physical
-events that are seen in other program time-lines; (2) the distinction
-between Blocked vs Stalled is that a Slave has to explicitly execute a
-VMS primitive operation to enter Blocked. In contrast, Stalled happens
-invisibly, with no effect on semantic behavior. It is due to hardware
-events hidden inside VMS, such as interrupts.
-
-The Ready state is used to separate the parallelism-construct behavior
-from the scheduling behavior. It acts as a ``staging area'' for
-scheduling. VPs placed into this state are {\em{ready}} to be
-animated, but the scheduler decides when and where.
-
-An interesting point is that in VMS, the causal tie between timelines is created by actions {\em{outside}}  program timelines. In contrast, memory-based lock algorithms place the concurrency-related behavior {\em{inside}} program
-timelines.
-
-\paragraph*{Transition Between Slave Scheduling States.}
-
-\begin{itemize}
-\item VPs transition states as shown in Figure \ref{figStates}.
-\item Animated$\rightarrow$Blocked is requested by a Slave  executing suspend, but takes place in Virtual time at the point the Master acknowledges that request.
-\item Blocked$\rightarrow$Ready is determined by the semantics
-  implemented in the plugin.
-\item Ready$\rightarrow$Animated is determined by the scheduler in the
-  plugin.
-\item Transitions in scheduling state have a globally consistent order
-  in Virtual time.
-\end{itemize}
-
-The parallelism primitives executed by a program do not directly control change
-in scheduling states. Rather they communicate messages to the Master,
-via a VMS supplied primitive. If it suspended when sending the request, then the act of the Master acknowledging the request places the Animated$\rightarrow$Blocked transition into Virtual time. Inside the Master, the plugin then processes the message. Based on contents, it performs changes in state from Blocked$\rightarrow$Ready,
-creates new VPs, and dissipates existing VPs.  Most communication from
-Slave to Master requires the Slave to suspend when it sends the
-message. A few messages, like creating new Slave may be sent without
-suspending.
-
-The suspend primitive decouples local physical time from Virtual time.
-Execution causes immediate transition to Stalled in physical time,
-later the Master performs Animated$\rightarrow$Blocked, fixing that
-transition in Virtual time. The only relationship is causality. This
-weak relation is what allows suspension-points to be serialized in
-Virtual time, which in turn is what allows using sequential algorithms
-to implement parallelism constructs.
-
-\subsection{Plugins}
-
-The Master entity has two parts, a generic core part and a plugin
-(Figure \ref{figMasterSplit}).  The core part of the Master is
-implemented as part of VMS itself. The plugin supplies two functions:
-the communication-handler and the scheduler, both having a standard
-prototype. The communication-handler implements the parallelism
-constructs, while scheduler assigns VPs to cores.
-
-An \emph{instance} of a plugin is created as part of initializing an
-application, and the instance holds the semantic and scheduling state
-for that run of the application. This state, combined with the virtual
-processor states of the slaves created during that application run,
-represents progress of the work of the application.  For example,
-multi-tasking is performed simply by the Master switching among
-plugin instances when it has a resource to offer to a scheduler. The
-parallelism-semantic state holds all information needed to resume
-(hardware state, such as TLB and cache-tags is inside VMS).
-
-\section{Internal Workings of Our Implementation}
-\label{secInternal}
-
-For our example implementation, we name the elements and describe their
-logical function, then relate those to the abstract model. We then step
-through the operation of the elements.
-
-\paragraph*{Elements and their logical function.}
-
-As illustrated in Figure~\ref{figInternals}, our VMS implementation is
-organized around physical cores.  Each core has its own {\em{master
-    virtual-processor}}, \texttt{masterVP}, and a {\em{physical-core
-    controller}}, which communicate via a set of scheduling slots,
-\texttt{schedSlot}. The Master in the abstract definition is
-implemented by the multiple \texttt{masterVP}s plus a particular
-plugin instance with its shared parallelism-semantic state (seen at
-the top).
-
-On a given core, only one of: the core-controller, \texttt{masterVP},
-or a slave VP, is animated at any point in local physical time. Each
-\texttt{masterVP} animates the same function, called
-\texttt{master\_loop}, and each slave VP animates a function from the
-application, starting with the top-level function the slave is created
-with, and following its call sequence. The core controller is
-implemented here as a Linux pthread that runs the \texttt{core\_loop}
-function.
-
-Switching between VPs is done by executing a VMS primitive that
-suspends the VP. This switches the physical core over to the
-controller, by jumping to the start of the \texttt{core\_loop}
-function, which chooses the next VP and switches to that (switching is
-detailed in Section \ref{secApp} Figure \ref{figAssembly}).
-
-\paragraph*{Relation to abstract model.}
-
-We chose to implement the Master entity of the model by a set of
-\texttt{masterVP}s, plus plugin functions and shared
-parallelism-semantic state. VMS consists of this implementation of the
-Master, plus the core-controllers, plus the VMS primitive libraries,
-for creating new VPs and dissipating existing VPs, suspending VPs, and
-communicating from slave VP to Master. In Figure~\ref{figInternals},
-everything in green is part of VMS, while the plugin is in red, and
-application code appears as blue, inside the slave VP.
-
-Virtual time in the model is implemented via a combination of four
-things: a \texttt{masterLock} (not shown) that guarantees non-overlap
-of \texttt{masterVP} trace-segments; the \texttt{master\_loop} which
-performs transition Animated$\rightarrow$Blocked; the
-\texttt{comm\_handler\_fn} which performs Blocked$\rightarrow$Ready
-and the \texttt{scheduler\_fn} which performs
-Ready$\rightarrow$Animated. \ Each state transition is one step of
-Virtual time; is guaranteed sequential by the non-overlap of
-\texttt{masterVP} trace segments; and is global due to being in
-parallelism-semantic state that is shared (top of
-Figure~\ref{figInternals}).
-
-Transitions Progressing$\rightleftarrows$Stalled within the Animated
-state are invisible to the parallelism semantics, the Master, and
-Virtual time, and so have no effect on the elements seen.
-
-\begin{figure*}[h!tb]
-  \centerline{\includegraphics[width=5in]{../figures/VMS-core__internal_workings.eps}}
-  \caption
-  { Internal elements of our example VMS implementation
-  }
-  \label{figInternals}
-\end{figure*}
-
-\paragraph*{Steps of operation.}
-
-The steps of operation are numbered, in Figure \ref{figInternals}.
-Taking them in order:
-
-\begin{enumerate}
-\item \texttt{master\_loop} scans the scheduling slots to see which
-  ones' slaves have suspended since the previous scan.
-\item It hands these to the \texttt{comm\_handler\_fn} plugged in
-(which equals transition Animated$\rightarrow$Blocked).
-\item The VP has a request attached, and data in it causes the
-  \texttt{comm\_handler\_fn} to manipulate data structures in the
-  shared parallelism-semantic state.  These structures hold all the
-  slaves in the blocked state (code-level detail and example will
-  come in Figure~\ref{figReqHdlr}, Section~\ref{secApp}).
-\item Some requests cause slaves to be moved to a \texttt{readyQ} on
-  one of the cores (Blocked$\rightarrow$Ready). Which core's
-  \texttt{readyQ} receives the slave is under plugin control,
-  determined by a combination of request contents, semantic state and
-  physical machine state.
-\item During the scan, the \texttt{master\_loop} also looks for empty
-  slots, and for each calls the \texttt{scheduler\_fn} plugged in. It
-  chooses a slave from the \texttt{readyQ} on the core animating
-  \texttt{master\_loop}.
-\item The \texttt{master\_loop} then places the slave VP's pointer
-  into the scheduling slot (Ready$\rightarrow$Animated), making it
-  available to the \texttt{core\_loop}.
-\item When done with the scan, \texttt{masterVP} suspends, switching
-  animation back to the \texttt{core\_loop}.
-\item \texttt{core\_loop} takes slave VPs out of the slots.
-\item Then \texttt{core\_loop} switches animation to these slave VPs.
-\item When a slave self-suspends, animation returns to the
-  \texttt{core\_loop} (detail in code in Figure 9), which picks
-  another.
-\item Until all slots are empty and the \texttt{core\_loop} switches
-  animation to the \texttt{masterVP}.
-\end{enumerate}
-
-\paragraph*{Enabling sequential implementation of parallelism semantics.}
-
-All these steps happen on each core separately, but
-%% AC. Cannot be both an essential property of VMS and "un this particular..."
-% in this particular implementation
-we use a central \texttt{masterLock} to ensure that
-only one core's \texttt{masterVP} can be active at any time.  This
-guarantees non-overlap of trace-segments from different
-\texttt{masterVP}s, allowing the plugins to use sequential algorithms,
-without a performance penalty, as verified in
-Section~\ref{secResults}.
-
-Relating this to the abstract model: the parallelism-semantic behavior
-of the Master is implemented by the communication handler, in the
-plugin. It thus runs in the Master time referred to, in the model, in
-Section \ref{secAbsModel}. Requests are sent to the Master by
-self-suspension of the slaves, but sit idle until the other slaves in
-the scheduling slots have also run. This is the passive behavior of
-requests that was noted in Section~\ref{secAbsModel}, which allows the
-\texttt{masterVP}s to remain suspended until needed.  This in turn
-enables the \texttt{masterVP}s from different cores to be
-non-overlapped. It is the non-overlap that enables the algorithms for
-the parallelism semantics to be sequential.
-
-\section{Code Example}
-\label{secApp}
-
-To relate the abstract model and the internal elements to application
-code and parallelism-library code, we give code snippets that
-illustrate key features.  We start with the application then work down
-through the sequence of calls, to the plugin, using our SSR
-{\cite{VMSHome}} parallelism-library as an example.
-
-In general, applications are either written in terms of a parallel
-language that has its own syntax, or a base language with a
-parallelism library, which is often called an {\em{embedded
-    language}}.  Our demonstrators, VCilk {\cite{VMSHome}}, Vthread,
-and SSR, are all parallelism libraries. A parallel language would
-follow the standard practice of performing source-to-source transform,
-from custom syntax into C plus parallelism-library calls.
-
-\paragraph*{SSR.}
-
-SSR stands for Synchronous Send-Receive, and details of its calls and
-internal implementation will be given throughout this section. It has
-two types of construct. The first, called {\em{from-to}} has two
-calls: \texttt{SSR\_send\_from\_to} and
-\texttt{SSR\_receive\_from\_to}, both of which specify the sending VP
-as well as the receiving VP. \ The other, called {\em{of-type}} also
-has two calls: \texttt{SSR\_\_send\_of\_type\_to} and
-\texttt{SSR\_\_receive\_of\_type}, which allow a receiver to accept
-from anonymous senders, but select according to type of message.
-
-% An example of a double column floating figure using two subfigures.
-% (The subfig.sty package must be loaded for this to work.)
-% The subfigure \label commands are set within each subfloat command, the
-% \label for the overall figure must come after \caption.
-% \hfil must be used as a separator to get equal spacing.
-% The subfigure.sty package works much the same way, except \subfigure is
-% used instead of \subfloat.
-%
-%\begin{figure*}[!t]
-%\centerline{\subfloat[Case I]\includegraphics[width=2.5in]{subfigcase1}%
-%\label{fig_first_case}}
-%\hfil
-%\subfloat[Case II]{\includegraphics[width=2.5in]{subfigcase2}%
-%\label{fig_second_case}}}
-%\caption{Simulation results}
-%\label{fig_sim}
-%\end{figure*}
-%
-% Note that often IEEE papers with subfigures do not employ subfigure
-% captions (using the optional argument to \subfloat), but instead will
-% reference/describe all of them (a), (b), etc., within the main caption.
-
-\paragraph*{Application view.}
-
-Figure~\ref{figAnimVP} shows snippets of application code, which use
-the SSR parallelism library. The most important feature is that all
-calls take a pointer to the VP that is animating the call. This is
-seen at the top of the figure where slave VP creation takes a pointer
-to the VP asking for creation. Below that is the standard prototype
-for top level functions, showing that the function receives a pointer
-to the VP it is the top level function for.
-
-The pointer is placed on the stack by VMS when it creates the VP, and
-is the means by which the application comes into possession of the
-pointer. This animating VP is passed to all library calls made from
-there. For example, the bottom shows a pointer to the animating VP
-placed in the position of sender in the \texttt{send} construct call.
-Correspondingly, for the \texttt{receive} construct, the position of
-receiving VP is filled by the VP animating the call.
-
-\begin{figure}[h!tb]
-{\noindent
-{\footnotesize
-{\small Creating a new processor:}
-\begin{verbatim}
-newProcessor = SSR__create_procr( &top_VP_fn, paramsPtr, animatingVP );
-\end{verbatim}
-
-{\small prototype for the top level function:}
-\begin{verbatim}
-top_VP_fn( void *parameterStrucPtr, VirtProcr *animatingVP );
-\end{verbatim}
-
-{\small handing animating VP to parallelism constructs:}
-\begin{verbatim}
-SSR__send_from_to( messagePtr, animatingVP, receivingVP );
-messagePtr = SSR__receive_from_to( sendingVP, animatingVP );
-\end{verbatim}
-}
-}
-\caption
-{Application code snippets showing that all calls to the parallelism library
-take the VP animating that call as a parameter.
-}
-\label{figAnimVP}
-\end{figure}
-
-Relating these to the internal elements of our implementation, the
-\texttt{animatingVP} suspends inside each of these calls, passing a
-request (generated in the library) to one of the \texttt{masterVP}s.
-The \texttt{masterVP} then calls the \texttt{comm-handler} plugin, and
-so on, as described in Section \ref{secInternal}.
-
-For the \texttt{SSR\_\_create\_processor} call, the comm-handler in
-turn calls a VMS primitive to perform the creation.  The primitive
-places a pointer to the newly created VP onto its stack, so that when
-\texttt{top\_VP\_fn} is later animated, it sees the VP-pointer as a
-parameter passed to it. \ All application code is either such a
-top-level function, or has one at the root of the call-stack.
-
-The send and receive calls both suspend their animating VP. When both
-have been called, the communication handler pairs them up and resumes
-both. This ties time-lines together, invoking the VMS guarantee. Both
-application-functions know, because of the VMS guarantee
-(Section~\ref{secAbsModel}), that writes to shared variables made
-before the send call by the sender are visible to the receiver after
-the receive call. This is the programmer's view of tying together the
-local time-lines of two different VPs, as defined in
-Section~\ref{secAbsModel}.
-
-\paragraph*{Concurrency-library view.}
-
-A parallelism library is a wrapper.  Each call, in general, only creates a request,
-sends it, and returns, as seen below.  To send a request, it uses the
-combined request-and-suspend VMS primitive that attaches the request
-then suspends the VP.  The primitive requires the pointer to the VP,
-to attach the request and to suspend it.
-
-In Figure~\ref{figImplLib}, notice that the request's data is on the
-stack of the virtual processor that's animating the call, which is the
-\texttt{receiveVP}.  The \texttt{VMS\_\_send\_sem\_request} suspends
-this VP, which changes the physical core's stack pointer to a
-different stack. So the request data is guaranteed to remain
-undisturbed while the VP is suspended.
-
-Figure~\ref{figAssembly} shows the implementation of the VMS suspend
-primitive. As seen in Figure \ref{figInternals}, suspending the
-\texttt{receiveVP} involves switching to the \texttt{core\_loop}. In
-our implementation, this is done by switching to the stack of the
-pthread pinned to the physical core and then jumping to the
-start-point of \texttt{core\_loop}.
-
-This code uses standard techniques commonly employed in co-routine
-implementations. Tuning effort spent in \texttt{core\_loop} is
-inherited by all applications.
-
-\begin{figure}[h!tb]
-{\noindent
-{\footnotesize
-\begin{verbatim}
-void * SSR__receive_from_to( VirtProcr *sendVP, VirtProcr *receiveVP )
- { SSRSemReq  reqData;
-   reqData.receiveVP = receiveVP;
-   reqData.sendVP    = sendVP;
-   reqData.reqType   = receive_from_to;
-   VMS__send_sem_request( &reqData, receiveVP );
-   return receiveVP->dataReturnedFromRequest;
- }
-\end{verbatim}
-}
-}
-\caption{Implementation of SSR's receive\_from\_to library function.}
-\label{figImplLib}
-
-{\noindent
-{\footnotesize
-\begin{verbatim}
-VMS__suspend_procr( VirtProcr *animatingVP )
- { animatingVP->resumeInstrAddr = &&ResumePt; //GCC takes addr of label
-   animatingVP->schedSlotAssignedTo->isNewlySuspended = TRUE; //for master_loop to see
-   <assembly code stores current physical core's stack reg into animatingVP struct>
-   <assembly code loads stack reg with core_loop stackPtr, which was saved into animatingVP>
-   <assembly code jmps to core_loop start instr addr, which was also saved into animatingVP>
- ResumePt:
-   return;
- }
-\end{verbatim}
-}
-}
-  \caption
-{Implementation of VMS suspend processor.
-Re-animating the virtual processor reverses this sequence. \ It saves the
-\texttt{core\_loop}'s resume instr-addr and stack ptr into the VP structure,
-then loads the VP's stack ptr and jmps to its \texttt{resumeInstrAddr}.
-}
-\label{figAssembly}
-
-{\noindent
-{\footnotesize
-\begin{verbatim}
-handle_receive_from_to( VirtProcr *requestingVP, SSRSemReq *reqData, SSRSemEnv *semEnv )
- { commHashTbl = semEnv->communicatingVPHashTable;
-   key[0] = reqData->receiveVP;   key[1] = reqData->sendVP; //send uses same key
-   waitingReqData = lookup_and_remove( key, commHashTbl );  //get waiting request
-   if( waitingReqData != NULL )
-    { resume_virt_procr( waitingReqData->sendVP );
-      resume_virt_procr( waitingReqData->receiveVP );
-    }
-   else
-      insert( key, reqData, commHashTbl ); //receive is first to arrive, make it wait
- }
-\end{verbatim}
-}
-}
-  \caption
-{Pseudo-code of communication-handler for
-\texttt{receive\_from\_to} request type. The \texttt{semEnv} is a pointer
-to the shared parallel semantic state seen at the top of
-Figure~\ref{figInternals}.
-}
-\label{figReqHdlr}
-\end{figure}
-
-\paragraph*{Plugin view.}
-
-SSR's communication handler dispatches on the \texttt{reqType} field
-of the request data, as set by the \texttt{SSR\_\_receive\_from\_to}
-code. It calls the handler code in Figure \ref{figReqHdlr}. This
-constructs a hash-key, by concatenating the from-VP's pointer with the
-to-VP's pointer. Then it looks-up that key in the hash-table that SSR
-uses to match sends with receives, which is in the shared semantic
-state seen at the top of Figure \ref{figInternals} in
-Section~\ref{secInternal}.
-
-The most important feature in Figure~\ref{figReqHdlr} is that both
-send and receive will construct the same key, so will find the same
-hash entry.  Whichever request is handled first in Virtual time will
-see the hash entry empty, and save itself in that entry.  The second
-to arrive sees the waiting request and then resumes both VPs, by
-putting them into their \texttt{readyQ}s.
-
-Access to the shared hash table can be considered private, as in a
-sequential algorithm.  This is because our VMS-core implementation
-ensures that only one handler on one core is executing at a time.
-
-\section{Results}
-\label{secResults}
-
-We implemented blocked dense matrix multiplication with right
-sub-matrices copied to transposed form, and ran it on a 4-core
-Core2Quad 2.4Ghz processor.
-
-\paragraph*{Implementation-time.}
-
-As shown in Table~\ref{tabPersonDaysLang}, time to implement the three
-parallel libraries averages 2 days each. As an example of
-productivity, adding nested transactions, parallel singleton, and
-atomic function-execution to SSR required a single afternoon, totaling
-less than 100 lines of C code.
-
-\paragraph*{Execution Performance.}
-
-Performance of VMS is seen in Table~\ref{tabOverheadCycles}. The code
-is not optimized, but rather written to be easy to understand and
-modify. The majority of the plugin time is lost to cache misses
-because the shared parallelism-semantic state moves between cores on a
-majority of accesses. Acquisition of the master lock is slow due to
-the hardware implementing the CAS instruction.
-
-Existing techniques will likely improve performance, such as
-localizing semantic data to cores, splitting malloc across the cores,
-pre-allocating slabs that are recycled, and pre-fetching. However, in
-many cases, several hundred nano-seconds per task is as optimal as the
-applications can benefit from.
-
-\begin{table}[h!tb]
-\begin{minipage}{.35\textwidth}
-\begin{tabular}{|l|l|l|l|}
-  \cline{2-4}
-  \multicolumn{1}{l|}{} & SSR & Vthread & VCilk\\
-  \cline{2-4}
-  \noalign{\vskip2pt}
-  \hline
-  Design & 4 & 1 & 0.5\\
-  Code & 2 & 0.5 & 0.5\\
-  Test & 1 & 0.5 & 0.5\\
-  L.O.C. & 470 & 290 & 310\\
-  \hline
-\end{tabular}
-\caption
-{Person-days to design, code, and
-  test each parallelism library. L.O.C. is lines of (original) C code,
-  excluding libraries and comments.
-}
-\label{tabPersonDaysLang}
-\end{minipage}
-\hspace{-.05\textwidth}
-\begin{minipage}[t]{.7\textwidth}
-\hfill
-\begin{tabular}{|l|l|r|r|}
-\cline{3-4}
-\multicolumn{2}{l|}{} & comp only & comp + mem\\
-\cline{3-4}
-\noalign{\vskip2pt}
-\hline
-VMS Only & \texttt{master\_loop} &  91 &  110\\
-& switch VPs  & 77 &  130\\
-& (malloc) & 160 & 2300\\
-& (create VP)  & 540 & 3800\\
-\hline
-Language: &  &  & \\
-\quad SSR & plugin -- concur & 190 & 540\\
-& plugin -- all & 530 & 2200\\
-& lock &  &  250\\
-\quad Vthread & plugin -- concur & 66 & 710\\
-& plugin -- all & 180 & 1500\\
-& lock &  &  250\\
-\quad VCilk & plugin -- concur & 65 & 260\\
-& plugin -- all & 330 & 1800\\
-& lock &  &  250\\
-\hline
-\end{tabular}
-\caption
-{Cycles of overhead, per scheduled
-    slave. ``comp only'' is perfect memory, ``comp + mem'' is actual cycles.
-    ``Plugin-concur'' only concurrency requests, ``plugin-all'' includes
-    create and malloc requests. Two significant digits due to variability.
-}
-\label{tabOverheadCycles}
-\end{minipage}
-
-\vskip-1.5cm
-\begin{tabular}{|l|lr|}
-\hline
-    Matrix size&Lang.&sec.\\
-[2pt]\hline
-    $81\times81$ & Cilk & 0.017\\
-    & VCilk & 0.008\\
-\hline
-    $324\times324$ & Cilk & 0.13\\
-    & VCilk & 0.13\\
-\hline
-    $648\times648$ & Cilk & 0.71\\
-    & VCilk & 0.85\\
-\hline
-    $1296\times1296$ & Cilk & 4.8\\
-    & VCilk & 6.2 \\
-[2pt]\hline
-\end{tabular}
-\hfill
-\begin{tabular}{|l|r|r|r|r|}
-\multicolumn{5}{l}{}\\
-\multicolumn{5}{l}{}\\
-\multicolumn{5}{l}{}\\
-\hline
-    operation & \multicolumn{2}{c|}{Vthread} & pthread & ratio\\
-    & comp only & total &  & \\
-[2pt]\hline
-    mutex\_lock & 85 & 1050 & 50,000 & 48:1\\
-    mutex\_unlock & 85 & 610 & 45,000 & 74:1\\
-    cond\_wait  & 85 & 850 & 60,000 & 71:1\\
-    cond\_signal & 90 & 650 & 60,000 & 92:1\\
-\hline
-\end{tabular}
-\caption
-{On left, exe time in seconds for MM. To the right, overhead for
-  pthread vs. Vthread. First column is cycles
-  for perfect memory and second is total measured cycles. pthread cycles are
-  deduced from round-trip experiments.
-}
-\label{tabHeadToHead}
-\end{table}
-
-\paragraph*{Head to head.}
-
-We compare our implementation of the \texttt{spawn} and \texttt{sync}
-constructs against Cilk 5.4, on the top in Table~\ref{tabHeadToHead},
-which shows that the same application code has similar
-performance. For large matrices, Cilk 5.4's better use of the memory
-hierarchy (the workstealing algorithm) achieves 23\% better
-performance. However, for small matrices, VCilk is better, with a
-factor 2 lower overhead. Cilk 5.4 does not allow controlling the
-number of spawn events it actually executes, and chooses to run
-smaller matrices sequentially, limiting our comparison.
-
-When comparing to pthreads, our VMS based implementation has more than
-an order of magnitude better overhead per invocation of mutex or
-condition variable functionality, as seen on the bottom of Table
-\ref{tabHeadToHead}.  Applications that inherently have short trace
-segments will synchronize often and benefit the most from Vthread.
-
-\section{Conclusion}
-\label{secConclusion}
-
-We have shown an alternative to the thread model that enables
-easier-to-use parallelism constructs by splitting the scheduler open,
-to accept new parallelism constructs in the form of plugins. This
-gives the language control over assigning virtual processors to
-physical cores, for performance, debugging, and flexibility
-benefits. Parallelism constructs of programming languages can be
-implemented using sequential algorithms, within a matter of days,
-while maintaining low run-time overhead.
-
-\bibliography{../helpers/bib_for_papers}
-
-\end{document}
- }
diff -r e455dad92745 -r bc4dd419ed1a 0__Papers/VMS/VMS__Foundation_Paper/LCPC_2011_Photo_Ready/latex/June_2011__Thread_replacement__Photo_Ready__LNCS.tex.Backup-20111205-164452
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-% correct bad hyphenation here
-\hyphenation{op-tical net-works semi-conduc-tor}
-
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-\begin{document}
-
-\bibliographystyle{plain}
-%
-
-\title{A Mutable Hardware Abstraction to Replace Threads}
-
-\author{Sean Halle\inst{1,2,3} \and Albert Cohen\inst{1}}
-\institute{INRIA and \'Ecole Normale Sup\'erieure, France
-  \and
-  University of California at Santa Cruz, USA
-  \and
-  Technical University Berlin}
-
-\maketitle             
-%
-
-\begin{abstract}
-  We propose an abstraction to alleviate the difficulty of programming
-  with threads. This abstraction is not directly usable by application
-  programmers.  Instead, application-visible behavior is defined
-  through a semantical plugin, and invoked via a language or library
-  that uses the plugin.  The main benefit is that parallel language
-  runtimes become simpler to implement, because they use sequential
-  algorithms for the parallel semantics. This is possible because the
-  abstraction makes available a virtual time in which events in
-  different program time-lines are sequentialized.  The parallel
-  semantics relate events in different time-lines via relating the
-  sequentialized versions within the virtual time-line.
-
-  We have implemented the abstraction in user-space and demonstrate
-  its low overhead and quickness to implement a runtime on three sets
-  of parallelism constructs: rendez-vous style \texttt{send} and
-  \texttt{receive}; Cilk style \texttt{spawn} and \texttt{sync}, which
-  have similar performance to Cilk 5.4; and \texttt{mutex} and
-  \texttt{condition variable} constructs from pthreads, which have 80x
-  lower overhead than Linux thread operations.  Development time
-  averaged around two days per set, versus an expected duration  of weeks to modify a thread-based runtime system.
-\end{abstract}
-
-\section{Motivation}
-
-Thread parallelism constructs have been well documented to be
-difficult to program with. They directly expose low-level concurrency
-to the programmer. Arbitrary non-deterministic behavior and deadlocks
-can arise from improperly synchronized code. Efficient execution
-requires non-blocking algorithms whose correctness require deep
-understanding of weakly consistent memory models. In addition, the
-operating system abstraction for threads comes with a very high
-context-switching and synchronization overhead.
-
-%% AC. The following is wrong.
-%\paragraph{\bf Problems with threads: } Thread parallelism constructs have been well documented to be difficult to program with. In addition, threads are problematic when one has multiple physical cores because the thread abstraction hides the hardware, disabling control over placement of tasks.  High performance requires such control. Hence, not only are threads  difficult to use directly in applications, but they prevent easier parallelism constructs from being built on top of them that have high performance.
-
-%\paragraph{\bf Partial solution: } To deal with this, in practice, a language's runtime turns off
-
-\paragraph*{A partial solution.}
-
-To deal with the last problem, a parallel language's runtime turns off
-operating system threads by pinning one to each physical core.  This
-way, the custom runtime is assured that the software thread is
-one-to-one with a physical core. It then implements a user-level
-thread package that lets it control which OS thread a computational
-task is assigned to. Finally, the runtime then implements the
-language's parallel semantics in terms of those user threads.
-
-The user-level threading approach addresses the system overhead issue,
-but it still hides important events such as input-output or
-node-to-node communications in a cluster.
-%% AC. Irrelevant for a parallelism-centric paper
-%software faults, and other hardware events
-Scalable runtimes need to coordinate task assignment
-to cores with application access of input and output, memory
-allocation over non-uniform cache and memory hierarchies, offloading
-to hardware accelerators, power management, and inter-node
-communication in a cluster.  The user-level threading approach is hampered in addressing these needs, and
-further makes the parallel runtime implementation cumbersome, error-prone and
-complex, because it is still written in terms of threads.
-
-
-Ideally, the OS would be in terms of a mutable hardware abstraction, and export mutations as new behavior.  We define a mutable hardware abstraction to be an interface to hardware-level behaviors that are normally inside the OS or below it. Examples include communication between cores, allotting time-slots to applications, and establishing ordering of events among cores (which is what atomic memory operations and equivalent patterns of instructions do).  The kernel itself would be implemented in terms of such an abstraction, and would accept mutations the same way it accepts device-drivers. It would then export the mutated behaviors for the language to trigger.
-
-A language  runtime would be in the form of a mutation. Being inside the OS, it has secure access to kernel-only hardware mechanisms. It could directly negotiate with the kernel to manage physical resources, in a low-overhead way.  The arrangement enables the runtime to control which task is assigned to which processing element at what time.  Both high performance and low-energy depend on this for implementing data affinity techniques. For example, the runtime could track data within the memory hierarchy and assign tasks to locations close to their consumed data.
-
-% \paragraph{\bf Support for portability: } This separation between
-% application executable and language runtime also supports
-% portability. It packages the language-specific scheduler into a
-% separate machine-specific module that is separately installed. The
-% scheduler is thus optimized for the combination of language with
-% hardware. This isn't a full solution to portability but it is a needed
-% precursor.
-
-% An interesting portability technique enabled by a separate
-% language-plus-hardware specific runtime is tracking which cores are
-% likely to already have data in the cache which a new task requires as
-% input. It could place tasks where the input data is likely to reside,
-% reducing communication to increase performance and power efficiency.
-
-\paragraph*{Contribution.}
-
-We show in this paper the definition and implementation of such a
-mutable hardware abstraction, albeit at user-level rather than in
-the kernel.  The abstraction lets a language's runtime be implemented as
-a mutation, which we call a plugin.  The plugin implements parallelism constructs and assignment of tasks to cores.
-
-We focus in this introductory paper on the definition of the
-abstraction and its support for parallelism constructs, postponing
-exploration of assignment of tasks onto cores and other performance
-optimizations to following papers. This paper defines multiple time-lines in a program, and a virtual timeline that globally orders events among them. It demonstrates three sets of parallelism constructs: synchronous \texttt{send}-\texttt{receive}
-motivated by process calculi; \texttt{spawn} and \texttt{sync} from
-Cilk {\cite{Fri98,CILKHome}}; and \texttt{mutex} and \texttt{condition
-  variable} from pthreads.  The assignment policy we implemented with
-them is simply first-come first-served.
-
-We call the abstraction Virtualized Master-Slave, or VMS. It
-exports facilities to create virtual processors and control how their timelines relate to each other, and relate to physical time. It also exports facilities to suspend a virtual processor and for an executable to interact with the plugin. The plugin embodies most of a language's runtime. A wrapper-library or keyword is what appears in application code, and is what triggers the runtime.
-
-\paragraph*{Organization of paper.}
-
-Section~\ref{secAbsModel} provide the original concepts and
-definitions of VMS. Section~\ref{secInternal} focuses on the
-implementation, describing the elements and how they interact, then
-relating them back to the theoretical definition.
-Section~\ref{secApp} takes the point of view of the application code,
-studying the usage and implementation of parallel language constructs
-as a VMS plugin. To wrap up, measurements of effectiveness appear in
-Section~\ref{secResults} and conclusions in
-Section~\ref{secConclusion}.
-
-\section{Background and Related Work}
-
-User-level thread packages and most parallel language runtimes have to
-side-step OS threads, by pinning one to each core, which effectively
-gives the user-level package control over the core. Our VMS
-implementation also does this. We are not claiming in this paper to
-have the OS level implementation of VMS that is possible -- but just
-the user-space version.
-
-\paragraph*{Related work.}
-
-The most primitive methods for establishing ordering among cores or distributed processors are atomic instructions and clock-synchronization techniques \cite{Lamport78,Christian89}.
-
-Meanwhile, the most closely related work is Scheduler Activations
-\cite{SchedActivations}, which also allows modifying concurrency
-constructs and controlling assignment of virtual processors onto
-cores. However it has no virtual time to guarantee globally consistent
-sequentialization, and no interface for plugins.
-
-BOM \cite{BOMinManticore}, which is used in Manticore to express
-scheduling policies and synchronization, also bears resemblances to
-VMS, but at a higher level of abstraction. BOM is a functional
-language, rather than a primitive abstraction meant to sit at the
-hardware-software boundary as VMS is.
-
-Coroutines is a high-performance means of switching between
-tasks. Coroutine scheduling and stack handling techniques were well
-suited to the user-space implementation of VMS.
-
-Other related work either provides an abstraction of the thread model,
-or is a full language with specific parallelism constructs. As a
-protypic example of user-level threads, Cilk {\cite{Fri98,CILKHome}}
-provides a simplified abstraction with an efficient scheduling and
-load balancing algorithm, but limited to fork-join concurrency. OpenMP
-{\cite{OpenMPHome}} is a typical example of a parallel extension of
-sequential languages; it allows creating tasks and controlling their
-execution order. We claim that both Cilk and OpenMP, as well as most
-thread abstractions or parallel languages may be implemented via
-plugins to VMS, with similar performance.
-
-VMS is unique in that it doesn't impose its own concurrency semantics as a programming model, but rather takes preferred ones as plugins. This
-makes it only a \emph{support} mechanism to
-implement language runtimes -- VMS is hidden from the application, underneath the language. Parallelism constructs may be implemented
-as VMS plugins, easily, quickly, and with high performance as
-indicated in Section~\ref{secResults}.
-
-This work presents a first incarnation  of VMS. We plan
-to explore the embedding into VMS of a variety of parallel languages,
-with a special interest for coordination languages
-\cite{Gelernter85Linda,CnCInHotPar,CnCHome}. We will also explore
-VMS's compatibility with different concurrent semantics
-\cite{Kah74,hoare78,milner99,Hewitt10,Actors97}. One particularly
-important application would be to use VMS to facilitate the design and
-implementation of the emerging hybrid programming models, such as
-MPI+OpenMP, or OpenMP+OpenCL \cite{Car10,OpenCLHome}.
-
-
-\section{Abstract Definition of VMS}
-\label{secAbsModel}
-
-We start with an intuitive overview, then precise the definitions and
-properties in the following sub-sections.
-
-\paragraph*{Definitions:}
-
-1) We want to avoid the confusion associated with the various
-interpretations for the terms ``thread'' and ``task'' so will use
-the term \emph{Virtual Processor} (VP), which we define as state in
-combination with the ability to animate code or an additional level of
-virtual processors. The state consists of a program counter, a stack
-with its contents, a pointer to top of stack, and a pointer to the
-current stack frame. 2) A \emph{physical processor}   executes
-a sequential stream of instructions.
-3) A program-timeline is the sequence of instructions animated by a
-Slave VP, which is in turn animated by a physical processor.
-
-
-\paragraph*{Intuitive Overview.}
-
-VMS can be understood via an analogy with atomic instructions, such as Compare and Swap (CAS). These are used to establish an ordering among the timelines of cores. They consist of two parts: 1) the semantics of what is done to the memory location, 2) a mechanism that establishes an ordering among the cores.  For CAS, the semantics are: ``compare value in this register to value at the address, and if same, then put value in second register into the address.''  Multiple kinds of atomic instructions share the same order-establishing mechanism, they simply provide different semantics as a front-end.
-
- VMS can be viewed as virtualizing the order-establishing mechanism. It allows the semantics to be plugged-in to it. This breaks concurrency constructs into two parts: the VMS mechanism, which establishes an ordering between events in different timelines; and the plugin, which supplies  the semantics.
-
- Below the interface, hardware mechanisms are employed to order specific points in one physical processor's timeline relative to specific points in another's timeline.    Above the interface, a plugin  provides the semantics that an application uses to invoke creation of the ordering. 
-
-Together,  VMS plus the plugin form a parallelism construct, by which an application controls how the time-lines of its virtual processors relate. Such constructs also guarantee relations of VP time-lines to hardware events.
-
-As an example, consider a program where one VP writes into a data structure then calls a \texttt{send} construct. Meanwhile, a
-different VP calls the \texttt{receive} construct then reads
-the data structure. The semantics of the \texttt{send} and \texttt{receive} constructs are that all data
-written before the \texttt{send} is readable in the other time-line
-after the \texttt{receive}.
- To implement these constructs, VMS provides the mechanism to enforce the ordering, and to include the writes and reads in that ordering.  The plugin directs that mechanism to order the \texttt{send} event before the \texttt{receive} event.
-%% AC. Too early.
-% VMS provides a primitive guarantee that
-% plugin code builds upon to provide such higher-level guarantees. The
-% primitive guarantee is defined in Section~\ref{scTime}, after the
-% necessary vocabulary is established.
-
-\paragraph{What the VMS interface provides:} The interface provides primitive operations
-to create and suspend VPs; a way for plugins to control when and where
-each VP is (re)started; a way for application code to send requests to the plugin; and a way to order a specific point in one VP time-line relative to a specific point in another VP time-line. All implementations of the VMS interface provide these, whether  it is on shared memory or distributed, with
-strong memory consistency or weak.
-
-\paragraph*{Specification in three parts.}
-
-We specify the observable behavior of a VMS system \emph{with plugins present}.  Hence,
-the specified behaviors remain valid with any parallelism construct
-implementable with VMS.  First we give the specification of a computation system that VMS is compatible with; then specify a notion of time and the key VMS guarantee; and lastly specify
-virtual processor scheduling states and transitions between them.
-
-%% AC. Too early, Master has not been defined. I renamed VMS-core into
-%% VMS afterwards, finding no ambiguity.
-% The Master mentioned in the definition is an abstract entity, with a
-% plugin present. In practice, this Master entity is implemented as part
-% of a core VMS, and plugins later added. This VMS-core is the hardware
-% abstraction. It hides the physical hardware behind an interface that
-% creates virtual processors and enforces well-defined time-behavior.
-
-\subsection{The Specifications for a VMS-compatible Computation System}
-
-\begin{itemize}
-\item An application creates multiple VPs, which are Slaves, each with an
-  independent time-line.
-\item A schedule of Slaves is generated by a Master entity, from
-  within a hidden time-line(s).
-\item A schedule is the  set of physical locations and time-points at which Slaves are
-  (re)animated.
-\item All semantic parallelism behavior is invoked by Slaves communicating
-  with the Master.
-\item A Slave communicates with the Master by using a VMS primitive,
-  which suspends  the Slave.
-\end{itemize}
-
-\paragraph{Where we define:}
- Semantic Parallelism Behavior is the actions taken by a parallelism construct, which establishes an ordering among events in different Slave timelines.
-
-
-\paragraph{Discussion:}  The key point is that
-\emph{scheduling is separated from the application code}. This is enforced by the schedule being generated in a time-line hidden from the application. The rest of the requirements are consequences of that separation.
-
-The Master entity appears as a single entity, to the slaves. However it may
-be implemented with multiple (hidden) timelines.  This is the approach taken in our initial implementation, which has several Master VPs hidden inside the VMS
-implementation.
-
- 
-
-
-%% AC. Calling memory a processing element only adds confusion.
-% {\bf Definitions:\ }VMS is intended only for hardware systems that
-% consist of processing elements connected by communication.  We define
-% a memory-space to be a processing element, albeit without the ability
-% to transform data.
-
-
-\subsection{The Time-Related Specifications of VMS}
-\label{secTime}
-
-To prepare for the time-related specifications, we give an advance peek of the following section, 3.3. There, Slave VPs are specified to have three scheduling states: Animated, Blocked, and Ready.  When a  parallelism construct starts execution, the Slave  transitions from Animated to Blocked. When it ends execution, the Slave transitions from Blocked to Ready.    VMS provides a way to control the order  of these state-transitions, which is equivalent to controlling the order of the parallelism-constructs.  Controlling the state transitions is how the ordering among constructs in different timelines  is established. 
-   
-With that background, here are time-related specifications for VMS: \begin{itemize}
-\item VMS provides a Virtual timeline that globally orders changes of scheduling state  of Slave VPs.
-\item Ordering is created among construct-invocations by controlling the order of Blocked to Ready transitions in the Virtual timeline.
-\item 
-Causally tied construct-invocations are  tied-together inside the Master. \item VMS enforces ordering of \textit{observations} of physical events  in Slave timelines to be consistent with the Virtual time ordering.
-\item Virtual time defines only ordering, but not spans, nor widths.
-\end{itemize}
-
-\paragraph{Discussion:} 
-Most importantly here, Virtual time defines a global ordering among Slave state-transitions. To make this useful for parallelism,  VMS must be implemented so that observations of physical events, like reads and writes to shared memory, are consistent with that ordering. 
-
-The Virtual timeline plays the same role as the mechanism added to memory systems to support atomic instructions. All atomic instructions require hardware that establishes an ordering among the timelines of physical cores. That hardware sequentializes execution of atomic memory accesses to the same address. VMS virtualizes this mechanism.  It provides the same ordering function.
-
-An important point is that the Virtual timeline is generated inside the Master. When a Slave uses the VMS primitive to send a parallelism-construct request, it suspends.  However, that Slave doesn't actually transition state from Animated to Blocked until the Master \textit{acknowledges} the suspension.  It is the  acknowledgement that adds the Slave transition into the Virtual timeline.
-
-The essential value of VMS is using it to control the order of observing events. It has to be able to causally link the execution of a parallelism construct in one timeline to the execution of a construct in a different timeline. Establishing such a causal link is called \textit{tying together} two construct executions.
- It is specific executions from different timelines that are causally linked with such a tie.
-\paragraph*{The key VMS guarantee:}
-
-the order of observing physical events is consistent with the order of tied together parallelism constructs. 
-
-To explain this, take as given:  two Slaves both execute parallelism constructs, those are tied together by the Master, establishing a causal ordering from one to the other. So, one construct is the \textit{before}-construct, the other is the \textit{after}-construct. Now, the guarantee means that any events triggered before the before-construct, in its timeline,   are guaranteed to be detected in the other timeline as also preceding the after-construct.  In addition, events triggered after the after-construct are guaranteed not visible before the before-construct in its timeline. This two-part guarantee is the result of the above specifications of VMS's time-related behavior.
-
-
-
- 
-\paragraph*{Definitions:}
-
-Some more definitions, to prepare for the next explanation. 1) An \textit{ordering-point} exists in a Slave VP's timeline as a zero-width event that can be tied to ordering points in other timelines. It is initiated by a Slave VP executing the suspend
-primitive, and ended by the Master transitioning the Slave back to Animated. 2) A trace-segment is a portion of a Slave VP's stream of instructions bounded by ordering-points. 
-
-Hence, the timeline of a Slave is a sequence of trace-segments. Each
-trace-segment is animated by a single physical processor, but not
-necessarily the same  as animated the Slave's other trace segments.
-
-  
-
-
-\begin{figure}[ht]
- \includegraphics[width=3.5in]{../figures/Time_in_VMS_2.eps}
- \caption
- {Time Behaviors:  \ Shows Ordering Point 1.1 being tied to Ordering Point 2.1. As a result, VMS guarantees that events triggered in Trace Segment 1.1 are seen as having taken place in the past in Trace Segment 2.2.  Also shows that there is no common tied ordering point between segments 1.2 and 2.2, so VMS provides no guarantees about what order segment 2.2 sees events triggered in segment 1.2.
-  }
-\label{figTimeMapping}
-\end{figure}
-
-\paragraph*{Relating time-lines to each other.}
-
-Figure \ref{figTimeMapping} shows two ordering points being tied together. A trace segment starts, at the same time an ordering-point ends, by its Slave transitioning to Animated.  Because the transition to Animated exists as a point in Virtual time, the start of a trace-segment has a well-defined position within Virtual time. Likewise, a trace-segment is ended by its Slave executing the suspend primitive of VMS.  Although this does not have a well-defined point in Virtual time, every execution of suspend is acknowledged by the Master, which transitions the Slave to Blocked.  That transition does have a well-defined position in Virtual time. Hence, the end of every trace-segment is associated with a well-defined position in Virtual time.
-
-As a result, trace segments can be ordered relative to each other, by checking their start and end points in Virtual time. If they have no overlap in virtual time then they have a total ordering. However, if any portion of them overlaps in Virtual time, then they are considered concurrent trace-segments, and their Slaves are considered to be executing in parallel between those points of Virtual time.  
-
-Note that this is conservative because it doesn't take into account the physical wait time between a Slave suspending and the Master acknowledging. The Slave may stop executing at a physical time-point that would map onto an earlier point in Virtual time. In some cases, ending the Slave's trace-segment at the earlier point would eliminate the overlap with a particular other trace-segment.  But VMS's set of specifications doesn't allow such mapping of suspend-execution onto Virtual time (for implementation-related reasons, which require downloading the code and gaining experience with it, to establish a common language, for an explanation to be understood).
-
-
-
-A  subtlety is that events triggered
-before one tied ordering-point, {\em{might}} be visible in the other timeline before the other tied ordering-point.  In the figure, segment 2.1 might be able to see events from segment 1.1 if it looked.  The VMS guarantee doesn't cover overlapped trace-segments. Physical events triggered before are only guaranteed visible
-{\em{after}} the tie point, and events after are only guaranteed
-{\em{not}} visible {\em{before}} the tie point.
-
-We call this bounded non-determinism, because events within overlapped trace-segments have non-deterministic ordering, but the region of non-determinism can be bounded by tied ordering-points. This allows a program to specify non-determinism, but control the region of non-deterministic behavior.  For example, a reduction construct could be created that non-deterministically assigns portions of the reduction work to overlapped Slave segments. It would tie together ordering points from all the Slaves that mark the end of reduction.  Hence, the outcome is deterministic, but the path to get there is not.
-
-\paragraph*{Sequential algorithms for parallel constructs.}
-The globally-consistent sequential order in Virtual time enables one
-of VMS's main benefits: sequential algorithms for parallel constructs.
-An implementation to
-tie ordering points together equals an implementation of parallel constructs. A plugin has an ordering of state transitions available, and chooses from those. Sequential algorithms rely on an ordering existing, while concurrent algorithms must include operations that establish an ordering.  Plugins have Virtual time ordering available, so they can use sequential algorithms.  
-\subsection{Specification of Scheduling State}
-
-Scheduling state is used in VMS to organize internal activity, for
-enforcing the guarantees.
-
-\begin{itemize}
-\item VPs have three scheduling states: {\em{Animated}},
-  {\em{Blocked}}, {\em{Ready}}; see Figure~\ref{figStates}.
-\item VPs in Animated are {\em{allowed}} to advance Program time with
-  (core-local) physical time.
-\item VPs in Blocked and Ready do not advance their Program time.
-\item Animated has two physical states: {\em{Progressing}} and
-  {\em{Stalled}}.
-\item VPs in Progressing advance Program time with (core-local)
-  physical time, those in Stalled do not (allowing non-semantic
-  suspend for hardware interrupts).
-\item Scheduling states are defined in Virtual time only.
-\item Progressing and Stalled are defined in (core-local) physical
-  time only; the distinction is invisible in Virtual time.
-\end{itemize}
-
-\begin{figure}[h!tb]
-\begin{minipage}{.55\textwidth}
-  \includegraphics[width=\textwidth]{../figures/Scheduling_states_2.eps}
-  \caption{Scheduling states of a slave VP in the VMS model. Animated, Blocked, and Ready are only defined in Virtual Time and only visible in the Master.  Progressing and Stalled are only visible in physical-processor local time, not visible in Virtual time.}
-  \label{figStates}
-\end{minipage}
-\hfill
-\begin{minipage}{.43\textwidth}
-  \includegraphics[width=\textwidth]{../figures/VMS-core__plugins.eps}
-  \caption
- {
-  The Master, split into a generic core and a language-specific plugin.
-  The core encapsulates the hardware and remains the same across applications.
-  The plugin implements the semantics of the parallelism-constructs.
- }
- \label{figMasterSplit}
-\end{minipage}
-\end{figure}
-
-
-Some important points: (1) only VPs Animated can trigger physical
-events that are seen in other program time-lines; (2) the distinction
-between Blocked vs Stalled is that a Slave has to explicitly execute a
-VMS primitive operation to enter Blocked. In contrast, Stalled happens
-invisibly, with no effect on semantic behavior. It is due to hardware
-events hidden inside VMS, such as interrupts.
-
-The Ready state is used to separate the parallelism-construct behavior
-from the scheduling behavior. It acts as a ``staging area'' for
-scheduling. VPs placed into this state are {\em{ready}} to be
-animated, but the scheduler decides when and where.
-
-An interesting point is that in VMS, the causal tie between timelines is created by actions {\em{outside}}  program timelines. In contrast, memory-based lock algorithms place the concurrency-related behavior {\em{inside}} program
-timelines.
-
-\paragraph*{Transition Between Slave Scheduling States.}
-
-\begin{itemize}
-\item VPs transition states as shown in Figure \ref{figStates}.
-\item Animated$\rightarrow$Blocked is requested by a Slave  executing suspend, but takes place in Virtual time at the point the Master acknowledges that request.
-\item Blocked$\rightarrow$Ready is determined by the semantics
-  implemented in the plugin.
-\item Ready$\rightarrow$Animated is determined by the scheduler in the
-  plugin.
-\item Transitions in scheduling state have a globally consistent order
-  in Virtual time.
-\end{itemize}
-
-The parallelism primitives executed by a program do not directly control change
-in scheduling states. Rather they communicate messages to the Master,
-via a VMS supplied primitive. If it suspended when sending the request, then the act of the Master acknowledging the request places the Animated$\rightarrow$Blocked transition into Virtual time. Inside the Master, the plugin then processes the message. Based on contents, it performs changes in state from Blocked$\rightarrow$Ready,
-creates new VPs, and dissipates existing VPs.  Most communication from
-Slave to Master requires the Slave to suspend when it sends the
-message. A few messages, like creating new Slave may be sent without
-suspending.
-
-The suspend primitive decouples local physical time from Virtual time.
-Execution causes immediate transition to Stalled in physical time,
-later the Master performs Animated$\rightarrow$Blocked, fixing that
-transition in Virtual time. The only relationship is causality. This
-weak relation is what allows suspension-points to be serialized in
-Virtual time, which in turn is what allows using sequential algorithms
-to implement parallelism constructs.
-
-\subsection{Plugins}
-
-The Master entity has two parts, a generic core part and a plugin
-(Figure \ref{figMasterSplit}).  The core part of the Master is
-implemented as part of VMS itself. The plugin supplies two functions:
-the communication-handler and the scheduler, both having a standard
-prototype. The communication-handler implements the parallelism
-constructs, while scheduler assigns VPs to cores.
-
-An \emph{instance} of a plugin is created as part of initializing an
-application, and the instance holds the semantic and scheduling state
-for that run of the application. This state, combined with the virtual
-processor states of the slaves created during that application run,
-represents progress of the work of the application.  For example,
-multi-tasking is performed simply by the Master switching among
-plugin instances when it has a resource to offer to a scheduler. The
-parallelism-semantic state holds all information needed to resume
-(hardware state, such as TLB and cache-tags is inside VMS).
-
-\section{Internal Workings of Our Implementation}
-\label{secInternal}
-
-For our example implementation, we name the elements and describe their
-logical function, then relate those to the abstract model. We then step
-through the operation of the elements.
-
-\paragraph*{Elements and their logical function.}
-
-As illustrated in Figure~\ref{figInternals}, our VMS implementation is
-organized around physical cores.  Each core has its own {\em{master
-    virtual-processor}}, \texttt{masterVP}, and a {\em{physical-core
-    controller}}, which communicate via a set of scheduling slots,
-\texttt{schedSlot}. The Master in the abstract definition is
-implemented by the multiple \texttt{masterVP}s plus a particular
-plugin instance with its shared parallelism-semantic state (seen at
-the top).
-
-On a given core, only one of: the core-controller, \texttt{masterVP},
-or a slave VP, is animated at any point in local physical time. Each
-\texttt{masterVP} animates the same function, called
-\texttt{master\_loop}, and each slave VP animates a function from the
-application, starting with the top-level function the slave is created
-with, and following its call sequence. The core controller is
-implemented here as a Linux pthread that runs the \texttt{core\_loop}
-function.
-
-Switching between VPs is done by executing a VMS primitive that
-suspends the VP. This switches the physical core over to the
-controller, by jumping to the start of the \texttt{core\_loop}
-function, which chooses the next VP and switches to that (switching is
-detailed in Section \ref{secApp} Figure \ref{figAssembly}).
-
-\paragraph*{Relation to abstract model.}
-
-We chose to implement the Master entity of the model by a set of
-\texttt{masterVP}s, plus plugin functions and shared
-parallelism-semantic state. VMS consists of this implementation of the
-Master, plus the core-controllers, plus the VMS primitive libraries,
-for creating new VPs and dissipating existing VPs, suspending VPs, and
-communicating from slave VP to Master. In Figure~\ref{figInternals},
-everything in green is part of VMS, while the plugin is in red, and
-application code appears as blue, inside the slave VP.
-
-Virtual time in the model is implemented via a combination of four
-things: a \texttt{masterLock} (not shown) that guarantees non-overlap
-of \texttt{masterVP} trace-segments; the \texttt{master\_loop} which
-performs transition Animated$\rightarrow$Blocked; the
-\texttt{comm\_handler\_fn} which performs Blocked$\rightarrow$Ready
-and the \texttt{scheduler\_fn} which performs
-Ready$\rightarrow$Animated. \ Each state transition is one step of
-Virtual time; is guaranteed sequential by the non-overlap of
-\texttt{masterVP} trace segments; and is global due to being in
-parallelism-semantic state that is shared (top of
-Figure~\ref{figInternals}).
-
-Transitions Progressing$\rightleftarrows$Stalled within the Animated
-state are invisible to the parallelism semantics, the Master, and
-Virtual time, and so have no effect on the elements seen.
-
-\begin{figure*}[h!tb]
-  \centerline{\includegraphics[width=5in]{../figures/VMS-core__internal_workings.eps}}
-  \caption
-  { Internal elements of our example VMS implementation
-  }
-  \label{figInternals}
-\end{figure*}
-
-\paragraph*{Steps of operation.}
-
-The steps of operation are numbered, in Figure \ref{figInternals}.
-Taking them in order:
-
-\begin{enumerate}
-\item \texttt{master\_loop} scans the scheduling slots to see which
-  ones' slaves have suspended since the previous scan.
-\item It hands these to the \texttt{comm\_handler\_fn} plugged in
-(which equals transition Animated$\rightarrow$Blocked).
-\item The VP has a request attached, and data in it causes the
-  \texttt{comm\_handler\_fn} to manipulate data structures in the
-  shared parallelism-semantic state.  These structures hold all the
-  slaves in the blocked state (code-level detail and example will
-  come in Figure~\ref{figReqHdlr}, Section~\ref{secApp}).
-\item Some requests cause slaves to be moved to a \texttt{readyQ} on
-  one of the cores (Blocked$\rightarrow$Ready). Which core's
-  \texttt{readyQ} receives the slave is under plugin control,
-  determined by a combination of request contents, semantic state and
-  physical machine state.
-\item During the scan, the \texttt{master\_loop} also looks for empty
-  slots, and for each calls the \texttt{scheduler\_fn} plugged in. It
-  chooses a slave from the \texttt{readyQ} on the core animating
-  \texttt{master\_loop}.
-\item The \texttt{master\_loop} then places the slave VP's pointer
-  into the scheduling slot (Ready$\rightarrow$Animated), making it
-  available to the \texttt{core\_loop}.
-\item When done with the scan, \texttt{masterVP} suspends, switching
-  animation back to the \texttt{core\_loop}.
-\item \texttt{core\_loop} takes slave VPs out of the slots.
-\item Then \texttt{core\_loop} switches animation to these slave VPs.
-\item When a slave self-suspends, animation returns to the
-  \texttt{core\_loop} (detail in code in Figure 9), which picks
-  another.
-\item Until all slots are empty and the \texttt{core\_loop} switches
-  animation to the \texttt{masterVP}.
-\end{enumerate}
-
-\paragraph*{Enabling sequential implementation of parallelism semantics.}
-
-All these steps happen on each core separately, but
-%% AC. Cannot be both an essential property of VMS and "un this particular..."
-% in this particular implementation
-we use a central \texttt{masterLock} to ensure that
-only one core's \texttt{masterVP} can be active at any time.  This
-guarantees non-overlap of trace-segments from different
-\texttt{masterVP}s, allowing the plugins to use sequential algorithms,
-without a performance penalty, as verified in
-Section~\ref{secResults}.
-
-Relating this to the abstract model: the parallelism-semantic behavior
-of the Master is implemented by the communication handler, in the
-plugin. It thus runs in the Master time referred to, in the model, in
-Section \ref{secAbsModel}. Requests are sent to the Master by
-self-suspension of the slaves, but sit idle until the other slaves in
-the scheduling slots have also run. This is the passive behavior of
-requests that was noted in Section~\ref{secAbsModel}, which allows the
-\texttt{masterVP}s to remain suspended until needed.  This in turn
-enables the \texttt{masterVP}s from different cores to be
-non-overlapped. It is the non-overlap that enables the algorithms for
-the parallelism semantics to be sequential.
-
-\section{Code Example}
-\label{secApp}
-
-To relate the abstract model and the internal elements to application
-code and parallelism-library code, we give code snippets that
-illustrate key features.  We start with the application then work down
-through the sequence of calls, to the plugin, using our SSR
-{\cite{VMSHome}} parallelism-library as an example.
-
-In general, applications are either written in terms of a parallel
-language that has its own syntax, or a base language with a
-parallelism library, which is often called an {\em{embedded
-    language}}.  Our demonstrators, VCilk {\cite{VMSHome}}, Vthread,
-and SSR, are all parallelism libraries. A parallel language would
-follow the standard practice of performing source-to-source transform,
-from custom syntax into C plus parallelism-library calls.
-
-\paragraph*{SSR.}
-
-SSR stands for Synchronous Send-Receive, and details of its calls and
-internal implementation will be given throughout this section. It has
-two types of construct. The first, called {\em{from-to}} has two
-calls: \texttt{SSR\_send\_from\_to} and
-\texttt{SSR\_receive\_from\_to}, both of which specify the sending VP
-as well as the receiving VP. \ The other, called {\em{of-type}} also
-has two calls: \texttt{SSR\_\_send\_of\_type\_to} and
-\texttt{SSR\_\_receive\_of\_type}, which allow a receiver to accept
-from anonymous senders, but select according to type of message.
-
-% An example of a double column floating figure using two subfigures.
-% (The subfig.sty package must be loaded for this to work.)
-% The subfigure \label commands are set within each subfloat command, the
-% \label for the overall figure must come after \caption.
-% \hfil must be used as a separator to get equal spacing.
-% The subfigure.sty package works much the same way, except \subfigure is
-% used instead of \subfloat.
-%
-%\begin{figure*}[!t]
-%\centerline{\subfloat[Case I]\includegraphics[width=2.5in]{subfigcase1}%
-%\label{fig_first_case}}
-%\hfil
-%\subfloat[Case II]{\includegraphics[width=2.5in]{subfigcase2}%
-%\label{fig_second_case}}}
-%\caption{Simulation results}
-%\label{fig_sim}
-%\end{figure*}
-%
-% Note that often IEEE papers with subfigures do not employ subfigure
-% captions (using the optional argument to \subfloat), but instead will
-% reference/describe all of them (a), (b), etc., within the main caption.
-
-\paragraph*{Application view.}
-
-Figure~\ref{figAnimVP} shows snippets of application code, which use
-the SSR parallelism library. The most important feature is that all
-calls take a pointer to the VP that is animating the call. This is
-seen at the top of the figure where slave VP creation takes a pointer
-to the VP asking for creation. Below that is the standard prototype
-for top level functions, showing that the function receives a pointer
-to the VP it is the top level function for.
-
-The pointer is placed on the stack by VMS when it creates the VP, and
-is the means by which the application comes into possession of the
-pointer. This animating VP is passed to all library calls made from
-there. For example, the bottom shows a pointer to the animating VP
-placed in the position of sender in the \texttt{send} construct call.
-Correspondingly, for the \texttt{receive} construct, the position of
-receiving VP is filled by the VP animating the call.
-
-\begin{figure}[h!tb]
-{\noindent
-{\footnotesize
-{\small Creating a new processor:}
-\begin{verbatim}
-newProcessor = SSR__create_procr( &top_VP_fn, paramsPtr, animatingVP );
-\end{verbatim}
-
-{\small prototype for the top level function:}
-\begin{verbatim}
-top_VP_fn( void *parameterStrucPtr, VirtProcr *animatingVP );
-\end{verbatim}
-
-{\small handing animating VP to parallelism constructs:}
-\begin{verbatim}
-SSR__send_from_to( messagePtr, animatingVP, receivingVP );
-messagePtr = SSR__receive_from_to( sendingVP, animatingVP );
-\end{verbatim}
-}
-}
-\caption
-{Application code snippets showing that all calls to the parallelism library
-take the VP animating that call as a parameter.
-}
-\label{figAnimVP}
-\end{figure}
-
-Relating these to the internal elements of our implementation, the
-\texttt{animatingVP} suspends inside each of these calls, passing a
-request (generated in the library) to one of the \texttt{masterVP}s.
-The \texttt{masterVP} then calls the \texttt{comm-handler} plugin, and
-so on, as described in Section \ref{secInternal}.
-
-For the \texttt{SSR\_\_create\_processor} call, the comm-handler in
-turn calls a VMS primitive to perform the creation.  The primitive
-places a pointer to the newly created VP onto its stack, so that when
-\texttt{top\_VP\_fn} is later animated, it sees the VP-pointer as a
-parameter passed to it. \ All application code is either such a
-top-level function, or has one at the root of the call-stack.
-
-The send and receive calls both suspend their animating VP. When both
-have been called, the communication handler pairs them up and resumes
-both. This ties time-lines together, invoking the VMS guarantee. Both
-application-functions know, because of the VMS guarantee
-(Section~\ref{secAbsModel}), that writes to shared variables made
-before the send call by the sender are visible to the receiver after
-the receive call. This is the programmer's view of tying together the
-local time-lines of two different VPs, as defined in
-Section~\ref{secAbsModel}.
-
-\paragraph*{Concurrency-library view.}
-
-A parallelism library is a wrapper.  Each call, in general, only creates a request,
-sends it, and returns, as seen below.  To send a request, it uses the
-combined request-and-suspend VMS primitive that attaches the request
-then suspends the VP.  The primitive requires the pointer to the VP,
-to attach the request and to suspend it.
-
-In Figure~\ref{figImplLib}, notice that the request's data is on the
-stack of the virtual processor that's animating the call, which is the
-\texttt{receiveVP}.  The \texttt{VMS\_\_send\_sem\_request} suspends
-this VP, which changes the physical core's stack pointer to a
-different stack. So the request data is guaranteed to remain
-undisturbed while the VP is suspended.
-
-Figure~\ref{figAssembly} shows the implementation of the VMS suspend
-primitive. As seen in Figure \ref{figInternals}, suspending the
-\texttt{receiveVP} involves switching to the \texttt{core\_loop}. In
-our implementation, this is done by switching to the stack of the
-pthread pinned to the physical core and then jumping to the
-start-point of \texttt{core\_loop}.
-
-This code uses standard techniques commonly employed in co-routine
-implementations. Tuning effort spent in \texttt{core\_loop} is
-inherited by all applications.
-
-\begin{figure}[h!tb]
-{\noindent
-{\footnotesize
-\begin{verbatim}
-void * SSR__receive_from_to( VirtProcr *sendVP, VirtProcr *receiveVP )
- { SSRSemReq  reqData;
-   reqData.receiveVP = receiveVP;
-   reqData.sendVP    = sendVP;
-   reqData.reqType   = receive_from_to;
-   VMS__send_sem_request( &reqData, receiveVP );
-   return receiveVP->dataReturnedFromRequest;
- }
-\end{verbatim}
-}
-}
-\caption{Implementation of SSR's receive\_from\_to library function.}
-\label{figImplLib}
-
-{\noindent
-{\footnotesize
-\begin{verbatim}
-VMS__suspend_procr( VirtProcr *animatingVP )
- { animatingVP->resumeInstrAddr = &&ResumePt; //GCC takes addr of label
-   animatingVP->schedSlotAssignedTo->isNewlySuspended = TRUE; //for master_loop to see
-   <assembly code stores current physical core's stack reg into animatingVP struct>
-   <assembly code loads stack reg with core_loop stackPtr, which was saved into animatingVP>
-   <assembly code jmps to core_loop start instr addr, which was also saved into animatingVP>
- ResumePt:
-   return;
- }
-\end{verbatim}
-}
-}
-  \caption
-{Implementation of VMS suspend processor.
-Re-animating the virtual processor reverses this sequence. \ It saves the
-\texttt{core\_loop}'s resume instr-addr and stack ptr into the VP structure,
-then loads the VP's stack ptr and jmps to its \texttt{resumeInstrAddr}.
-}
-\label{figAssembly}
-
-{\noindent
-{\footnotesize
-\begin{verbatim}
-handle_receive_from_to( VirtProcr *requestingVP, SSRSemReq *reqData, SSRSemEnv *semEnv )
- { commHashTbl = semEnv->communicatingVPHashTable;
-   key[0] = reqData->receiveVP;   key[1] = reqData->sendVP; //send uses same key
-   waitingReqData = lookup_and_remove( key, commHashTbl );  //get waiting request
-   if( waitingReqData != NULL )
-    { resume_virt_procr( waitingReqData->sendVP );
-      resume_virt_procr( waitingReqData->receiveVP );
-    }
-   else
-      insert( key, reqData, commHashTbl ); //receive is first to arrive, make it wait
- }
-\end{verbatim}
-}
-}
-  \caption
-{Pseudo-code of communication-handler for
-\texttt{receive\_from\_to} request type. The \texttt{semEnv} is a pointer
-to the shared parallel semantic state seen at the top of
-Figure~\ref{figInternals}.
-}
-\label{figReqHdlr}
-\end{figure}
-
-\paragraph*{Plugin view.}
-
-SSR's communication handler dispatches on the \texttt{reqType} field
-of the request data, as set by the \texttt{SSR\_\_receive\_from\_to}
-code. It calls the handler code in Figure \ref{figReqHdlr}. This
-constructs a hash-key, by concatenating the from-VP's pointer with the
-to-VP's pointer. Then it looks-up that key in the hash-table that SSR
-uses to match sends with receives, which is in the shared semantic
-state seen at the top of Figure \ref{figInternals} in
-Section~\ref{secInternal}.
-
-The most important feature in Figure~\ref{figReqHdlr} is that both
-send and receive will construct the same key, so will find the same
-hash entry.  Whichever request is handled first in Virtual time will
-see the hash entry empty, and save itself in that entry.  The second
-to arrive sees the waiting request and then resumes both VPs, by
-putting them into their \texttt{readyQ}s.
-
-Access to the shared hash table can be considered private, as in a
-sequential algorithm.  This is because our VMS-core implementation
-ensures that only one handler on one core is executing at a time.
-
-\section{Results}
-\label{secResults}
-
-We implemented blocked dense matrix multiplication with right
-sub-matrices copied to transposed form, and ran it on a 4-core
-Core2Quad 2.4Ghz processor.
-
-\paragraph*{Implementation-time.}
-
-As shown in Table~\ref{tabPersonDaysLang}, time to implement the three
-parallel libraries averages 2 days each. As an example of
-productivity, adding nested transactions, parallel singleton, and
-atomic function-execution to SSR required a single afternoon, totaling
-less than 100 lines of C code.
-
-\paragraph*{Execution Performance.}
-
-Performance of VMS is seen in Table~\ref{tabOverheadCycles}. The code
-is not optimized, but rather written to be easy to understand and
-modify. The majority of the plugin time is lost to cache misses
-because the shared parallelism-semantic state moves between cores on a
-majority of accesses. Acquisition of the master lock is slow due to
-the hardware implementing the CAS instruction.
-
-Existing techniques will likely improve performance, such as
-localizing semantic data to cores, splitting malloc across the cores,
-pre-allocating slabs that are recycled, and pre-fetching. However, in
-many cases, several hundred nano-seconds per task is as optimal as the
-applications can benefit from.
-
-\begin{table}[h!tb]
-\begin{minipage}{.35\textwidth}
-\begin{tabular}{|l|l|l|l|}
-  \cline{2-4}
-  \multicolumn{1}{l|}{} & SSR & Vthread & VCilk\\
-  \cline{2-4}
-  \noalign{\vskip2pt}
-  \hline
-  Design & 4 & 1 & 0.5\\
-  Code & 2 & 0.5 & 0.5\\
-  Test & 1 & 0.5 & 0.5\\
-  L.O.C. & 470 & 290 & 310\\
-  \hline
-\end{tabular}
-\caption
-{Person-days to design, code, and
-  test each parallelism library. L.O.C. is lines of (original) C code,
-  excluding libraries and comments.
-}
-\label{tabPersonDaysLang}
-\end{minipage}
-\hspace{-.05\textwidth}
-\begin{minipage}[t]{.7\textwidth}
-\hfill
-\begin{tabular}{|l|l|r|r|}
-\cline{3-4}
-\multicolumn{2}{l|}{} & comp only & comp + mem\\
-\cline{3-4}
-\noalign{\vskip2pt}
-\hline
-VMS Only & \texttt{master\_loop} &  91 &  110\\
-& switch VPs  & 77 &  130\\
-& (malloc) & 160 & 2300\\
-& (create VP)  & 540 & 3800\\
-\hline
-Language: &  &  & \\
-\quad SSR & plugin -- concur & 190 & 540\\
-& plugin -- all & 530 & 2200\\
-& lock &  &  250\\
-\quad Vthread & plugin -- concur & 66 & 710\\
-& plugin -- all & 180 & 1500\\
-& lock &  &  250\\
-\quad VCilk & plugin -- concur & 65 & 260\\
-& plugin -- all & 330 & 1800\\
-& lock &  &  250\\
-\hline
-\end{tabular}
-\caption
-{Cycles of overhead, per scheduled
-    slave. ``comp only'' is perfect memory, ``comp + mem'' is actual cycles.
-    ``Plugin-concur'' only concurrency requests, ``plugin-all'' includes
-    create and malloc requests. Two significant digits due to variability.
-}
-\label{tabOverheadCycles}
-\end{minipage}
-
-\vskip-1.5cm
-\begin{tabular}{|l|lr|}
-\hline
-    Matrix size&Lang.&sec.\\
-[2pt]\hline
-    $81\times81$ & Cilk & 0.017\\
-    & VCilk & 0.008\\
-\hline
-    $324\times324$ & Cilk & 0.13\\
-    & VCilk & 0.13\\
-\hline
-    $648\times648$ & Cilk & 0.71\\
-    & VCilk & 0.85\\
-\hline
-    $1296\times1296$ & Cilk & 4.8\\
-    & VCilk & 6.2 \\
-[2pt]\hline
-\end{tabular}
-\hfill
-\begin{tabular}{|l|r|r|r|r|}
-\multicolumn{5}{l}{}\\
-\multicolumn{5}{l}{}\\
-\multicolumn{5}{l}{}\\
-\hline
-    operation & \multicolumn{2}{c|}{Vthread} & pthread & ratio\\
-    & comp only & total &  & \\
-[2pt]\hline
-    mutex\_lock & 85 & 1050 & 50,000 & 48:1\\
-    mutex\_unlock & 85 & 610 & 45,000 & 74:1\\
-    cond\_wait  & 85 & 850 & 60,000 & 71:1\\
-    cond\_signal & 90 & 650 & 60,000 & 92:1\\
-\hline
-\end{tabular}
-\caption
-{On left, exe time in seconds for MM. To the right, overhead for
-  pthread vs. Vthread. First column is cycles
-  for perfect memory and second is total measured cycles. pthread cycles are
-  deduced from round-trip experiments.
-}
-\label{tabHeadToHead}
-\end{table}
-
-\paragraph*{Head to head.}
-
-We compare our implementation of the \texttt{spawn} and \texttt{sync}
-constructs against Cilk 5.4, on the top in Table~\ref{tabHeadToHead},
-which shows that the same application code has similar
-performance. For large matrices, Cilk 5.4's better use of the memory
-hierarchy (the workstealing algorithm) achieves 23\% better
-performance. However, for small matrices, VCilk is better, with a
-factor 2 lower overhead. Cilk 5.4 does not allow controlling the
-number of spawn events it actually executes, and chooses to run
-smaller matrices sequentially, limiting our comparison.
-
-When comparing to pthreads, our VMS based implementation has more than
-an order of magnitude better overhead per invocation of mutex or
-condition variable functionality, as seen on the bottom of Table
-\ref{tabHeadToHead}.  Applications that inherently have short trace
-segments will synchronize often and benefit the most from Vthread.
-
-\section{Conclusion}
-\label{secConclusion}
-
-We have shown an alternative to the thread model that enables
-easier-to-use parallelism constructs by splitting the scheduler open,
-to accept new parallelism constructs in the form of plugins. This
-gives the language control over assigning virtual processors to
-physical cores, for performance, debugging, and flexibility
-benefits. Parallelism constructs of programming languages can be
-implemented using sequential algorithms, within a matter of days,
-while maintaining low run-time overhead.
-
-\bibliography{../helpers/bib_for_papers}
-
-\end{document}
- }
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