# HG changeset patch
# User Some Random Person <seanhalle@yahoo.com>
# Date 1334593658 25200
# Node ID b793b4934cf8aff4ca1e28ac93330c11cf265376
# Parent  556a9b80cdb5f1161715d41f01d6f10aaf02edf2
Added WorkTable paper

diff -r 556a9b80cdb5 -r b793b4934cf8 0__Papers/Work_Table/BLIS_WT_tutorial_with_building_house_analogy.pdf
Binary file 0__Papers/Work_Table/BLIS_WT_tutorial_with_building_house_analogy.pdf has changed
diff -r 556a9b80cdb5 -r b793b4934cf8 0__Papers/Work_Table/BLIS_WT_tutorial_with_building_house_analogy.tm
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/0__Papers/Work_Table/BLIS_WT_tutorial_with_building_house_analogy.tm	Mon Apr 16 09:27:38 2012 -0700
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+<TeXmacs|1.0.6.5>
+
+<style|article>
+
+<\body>
+  <doc-data|<doc-title|How to Write a Parallel Program Using
+  the<next-line>BLIS WorkTable Patterns>|<doc-author-data|<author-name|Sean
+  Halle>>>
+
+  <paragraph|Hello,>welcome to the tutorial for using the BLIS Work Table
+  patterns to create a parallel program. \ 
+
+  As an application programmer, your job is to make a system, that you can
+  hand to a crew of workers, who follow the instructions in your system,
+  resulting in a completed job. \ The BLIS Work Table patterns let you make a
+  system that any size of crew can use, to work together, keeping everyone
+  busy, without making any mistakes. \ None of the workers has to think about
+  anything, they just have to follow the instructions you wrote down on
+  pieces of paper, plus the BLIS Work Table way of doing things.
+
+  Okay, ready to start? \ The first thing you need to know to make your own
+  system is what a bit of work looks like. \ In BLIS Work Table, it's a list
+  of instructions plus a box holding the stuff to perform the instructions
+  on. \ A worker gets a list plus a box and follows the list on the contents
+  of the box. \ At the end, the contents of the box has changed, the change
+  is the work that was accomplished.
+
+  So, how to organize these bits of work? \ In BLIS Work Table, to make
+  organizing easier, instead of moving boxes around, we'll put a number on
+  each box, then write that number on a piece of paper and move the paper
+  around, call the piece of paper a box-paper. \ The box-papers get put into
+  piles, with attached to each pile a list of instructions. \ All the boxes,
+  named by the box-papers in the pile, have that same list of instructions
+  done to them. \ The piles get laid out on the Work Table, with arrows going
+  between them. \ When the instructions from one pile have been completed on
+  a box, its piece of paper follows the arrow to a new pile.
+
+  To do a unit of work, take a copy of the instructions, plus a box-paper, go
+  get the box, then follow the instructions on the contents. \ We'll call the
+  list of instructions plus the box named by a box-paper a WorkUnit, and
+  we'll call the box containing the materials a WorkUnit Box.
+
+  So, what's inside a box? \ A WorkUnit Box (WUB) holds all the materials,
+  plus notes from previous work done on those materials, like post-it notes
+  to let later work-units know about things. \ Let's say we're writing a
+  system for a team of workers to build a house. \ During construction, the
+  parts of the house can't actually be put into the box, so instead, a ticket
+  representing ownership of the material is put into the box, like a ticket
+  that owns ``the south wall''. \ Only boxes that have a ticket for part of
+  the house can do work on that part of the house. \ 
+
+  Let's say, a box-paper lands in the ``put in window'' pile, the box will
+  contain a ticket that owns a wall in the house, plus a ticket that owns one
+  of the windows sitting in the storage lot. \ The reason for the tickets is
+  to give us a way to make sure two workers don't try to use the same
+  material for two different bits of work at the same time! \ We'll see more
+  about keeping the workers out of each other's hair soon.
+
+  Great, now we have a box that holds all of the tickets for the materials
+  used in the work, and we have piles that have the instructions for what to
+  do on the materials, and we have a table to organize it all, how does the
+  work actually happen?
+
+  BLIS provides the table, and a person who sits at the table and does the
+  moving the box-papers among the piles. \ We'll call them the Scheduler
+  Person, or just the Scheduler. \ A worker walks up to the table, and the
+  Scheduler Person hands them a list of instructions plus a box-paper. \ The
+  worker walks off, finds the box, and follows the instructions on the
+  materials owned by the box. \ When done, they hand the box-paper back to
+  the Scheduler person, who follows the arrows, puts the paper in a new pile,
+  then picks another set of instructions plus box-paper and hands it to the
+  worker, and so on. \ Because the Scheduler Person is part of the BLIS Work
+  Table system, you, the programmer, don't know what choices they will make,
+  but you <em|can> tell them constraints on their choices, more on that
+  later.
+
+  That's \ the basic idea of how a system is used. \ As a programmer, your
+  task is to state the piles needed, draw the arrows between the piles, and
+  write the instructions for each pile. \ When done, you'll have a system for
+  making the thing you want made, and any crew of workers will be able to
+  show up and make one, no matter how many people they might have!
+
+  \;
+
+  <paragraph|Let's work through an example>of making such a system for
+  building a house. \ As a programmer, the first thing you write is the
+  instructions that tell the scheduler person how to set up the table,
+  including what piles to make, the arrows between the piles, and the
+  instructions to put at each pile. \ When the program starts, these setup
+  instructions run first. \ After the table is set up, the scheduler person
+  starts picking box-papers from the piles and handing them to workers, with
+  a copy of the pile-instructions, then getting box-papers back from the
+  workers, following the arrows to put those into the appropriate piles, and
+  repeating the picking and handing out, until the job is done.
+
+  The instructions for how to set up the table is called the ``setup''
+  function. \ In setup, you'll use built-in functions that start with
+  ``BLIS_WT__'', to tell the scheduler person the name and type of each pile
+  (BLIS_WT__create_work_pile...), the pile-instructions (a standard C
+  function), and the arrows between the piles
+  (BLIS_WT__connect_pile_to_pile...).
+
+  Like this:
+
+  BLIS_WT__start_work_table_setup( WT_FOR_HOUSE_CONSTRUCTION );
+
+  BLIS_WT__create_work_pile( FRAME_A_WALL, &make_the_frame_for_a_wall);
+
+  BLIS_WT__create_work_pile( PUT_IN_WINDOW, &put_window_into_wall);
+
+  BLIS_WT__create_work_pile(PUT_IN_DOOR, &put_door_into_wall);
+
+  BLIS_WT__connect_pile_to_pile( ENTRY, FRAME_A_WALL);
+
+  BLIS_WT__connect_pile_to_pile(FRAME_A_WALL, PUT_IN_WINDOW);
+
+  BLIS_WT__connect_pile_to_pile(PUT_IN_WINDOW, PUT_IN_DOOR);
+
+  BLIS_WT__end_work_table_setup( WT_FOR_HOUSE_CONSTRUCTION);
+
+  \;
+
+  When creating a pile, the first argument is the name of the pile, as an
+  enum constant, the second is the pile-instructions, a pointer to a
+  function. \ When connecting piles, the first argument is the name of the
+  from-pile, the second the name of the to-pile. \ Notice, this work table
+  arrangement only has parallelism for doing multiple walls at the same time.
+  \ On a single wall, the work goes in-order, frame, then put in windows,
+  then put in door. \ This shortcoming will be fixed with the new kinds of
+  piles introduced next.
+
+  \;
+
+  <paragraph|Not all piles are the same,>some are special, used only by the
+  scheduler person, in effect to make sure no two workers interfere with each
+  other, while still keeping all workers busy. \ For example, going back to
+  installing a window, imagine that one of the workers took the window and
+  tried to install it before the wall was finished! \ Or, that a worker
+  painted the wall before the window was in, which would leave the window
+  frame unpainted! \ 
+
+  To prevent these problems, there are piles called ``hold until'' -- a
+  box-paper is held in one of these piles until something happens that
+  releases it. \ The instructions that go with a HoldUntil pile get performed
+  by the scheduler person, and tell them, for a given box-paper that comes
+  in, which releasing box-paper to watch for and where to watch for it (or
+  them, because sometimes a held box-paper has multiple propendent
+  box-papers).\ 
+
+  In this example, let's say when a wall is done, that two box-papers are
+  made for the WUB that owns it, one box-paper goes to a pile where all the
+  windows get put into the wall, the other box-paper goes to the pile where
+  the wall gets painted. \ If the second box-paper goes right in, it might
+  get handed to a worker too early! \ It's only when a box-paper leaves the
+  ``Install windows'' pile, that the box-paper for the same box can leave the
+  ``hold until windows installed'' pile and flow into the ``paint'' pile.
+  \ \ 
+
+  One complication is that the scheduler person has to do some bookkeeping
+  when watching for propendent box-papers. \ So for each spot that a
+  HoldUntil might tell the scheduler person to watch, a Watcher is created,
+  which causes a place to be setup for the scheduler person to keep track of
+  which box-papers have passed that spot.\ 
+
+  Here's what the setup code for such a HoldUntil would look like:
+
+  BLIS_WT__create_Watcher_at_pile_exit(INSTALL_WINDOWS,INSTALL_WINDOWS_EXIT);
+
+  BLIS_WT__create_HoldUntil_pile(HOLD_FOR_WINDOWS,
+  &calc_ID_of_releasing_box);
+
+  BLIS_WT__connect_pile_to_pile(HOLD_FOR_WINDOWS, PAINT_WALL);
+
+  \;
+
+  The first line creates a watcher -- the first arg is the pile-exit to
+  watch, the second is the watcher's name. \ The second line creates the
+  HoldUntil -- the first argument is the name of the pile, the second is a
+  pointer to a C function that calculates which WorkUnit Box is being waited
+  upon, and where to watch for it. \ This function will use the name of the
+  watcher that was created on the first line.
+
+  \;
+
+  Another kind of scheduler pile is called a ReJoiner. \ Sometimes, two
+  different materials will have things done to them separately, but they have
+  to join up again and be used together. \ For example, a door fits to a
+  particular frame, the two get given to two different work unit boxes, and
+  separately get sanded down, primed, and stained. \ When both are done, the
+  door has to be joined back together with its frame, so a ReJoiner pile is
+  made that matches the work-unit box that owns the door to the work-unit box
+  that owns the frame. \ You, the programmer, write a function that takes a
+  box and calculates a ``match number'' for it. \ The Scheduler Person
+  sitting at the table will take the match_number function you write and use
+  it to find pairs of work-unit-boxes. \ They put the pairs, together, onto
+  the next pile.
+
+  Continuing the example, to let doors and their frames be worked on
+  separately, one of the piles has to separate them! \ The pile that does
+  this will receive the door + frame as a unit, and has two choices on how to
+  proceed -- the first is to make two new work-unit-boxes and give one
+  ownership of the door, the other ownership of the frame, then send those
+  two along different arrows. \ The second is to make a copy of the piece of
+  paper with the ID of the work-unit box, then send one copy down the path
+  for doors and the other copy down the path for frames. \ 
+
+  The second option is less work, so try that. \ At the spot on the table
+  where the two paths come back together, place a ReJoiner, which will have
+  two inputs, one from each path. \ To each input attach a function that just
+  takes the ID of the work-unit-box and returns that as the match-ID. \ This
+  will cause one copy of the paper with the work-unit-box ID to be matched
+  with the other copy. \ This way, it's certain that <em|both> the door and
+  the frame have completed before doing any more work with them.
+
+  Here's the code:
+
+  BLIS_WT__ (dispatch pile to two others -- a sand door pile and a sand frame
+  pile -- then a ReJoiner pile)
+
+  dispatch pile -- takes ``house materials'', outputs ``doors'',
+  ``door-frames'', ``windows'', ``materials''
+
+  BLIS_WT__(ReJoiner pile made with the make-match-ID function for each input
+
+  (show function that extracts ID and returns as match_ID)
+
+  \;
+
+  \;
+
+  The next scheduler pile is called a Keeper pile, which keeps around
+  work-unit boxes that <em|might> be needed at some point. \ As an example,
+  say one of the work-piles makes a special jig for cutting the holes in a
+  door to install a door-knob. \ Some of the doors arrive with the door-knob
+  already installed, so it's not certain which doors will need the jig. \ A
+  separate jig is made for each kind of door, and when complete, the jig
+  flows into a Keeper. \ More precisely, a ticket for the jig is put into a
+  work-unit box and the box-paper for that box flows into the Keeper-pile. \ 
+
+  We will need some way to steer box-papers, in this case either sending to
+  the Keeper so a door-knob can be installed, or by-passing the
+  door-knob-install process. \ Another kind of scheduler pile gets used for
+  this, called a Steer-pile. \ The instructions for one of these tell the
+  scheduler person which of many outputs to send a box-paper on. \ All
+  work-piles have only a single output spot, so a Steer-pile is needed to
+  steer a box-paper among many possible routes.
+
+  Continuing the example, let's say the box-paper for a door flows into a
+  work-pile. \ The instructions say to check if the door has a knob
+  installed. \ The worker looks, and this door is missing the knob, so the
+  instructions tell the worker to write a post-it note saying the box needs a
+  knob installed, and another post-it saying the type of door. \ The
+  instructions say where to put these notes in the box.
+
+  From there, the box-paper flows into a Steer-pile, where the instructions
+  tell the scheduler person to look inside the work-unit box and find the
+  post-it left there by the worker. \ If the note says the door needs a knob
+  installed, it flows out the ``need knob'' output, otherwise it flows out
+  the ``has a knob'' output.
+
+  The ``needs knob'' output was connected to the request-pile of the Keeper
+  that has the jigs, where the instructions say to get the post-it that has
+  the kind of door written on it. \ The instructions then have a numbered
+  list and tell the scheduler person to match the name on the post-it to a
+  name in the list, then look at the list number. \ This number is the ID of
+  the work-unit-box that owns the jig needed for that kind of door!
+
+  At this point, the scheduler person goes and checks if the work-unit-box
+  with that ID on it is sitting in the Keeper room. \ If not, they leave a
+  note for themselves, which they'll check when putting work-unit-boxes into
+  the room. \ Either way, whenever the work-unit box is in the room, the
+  scheduler person sees it and puts its box-paper together with the box-paper
+  from the request-pile, and flows them out of the Keeper along the arrow
+  leaving the Keeper's ``response'' output. \ In this example, the pointed-to
+  will to be the work-pile for installing a door-knob!
+
+  When the door-knob installation is complete, the work-unit box that owns
+  the jig gets sent back to the Keeper-pile. \ When it arrives, the scheduler
+  person checks their notes whether any requests are waiting for that
+  work-unit box.
+
+  Notice that the scheduler person is the only one with access to the Keeper
+  room, so the scheduler alone controls which request-response pairs have a
+  box-paper for a box that's in the Keeper room. \ The way the scheduler
+  person keeps track of this requires more depth to explain, but the
+  end-effect is that the scheduler can be told to control Kept boxes in a few
+  different ways: ensure that the Kept work-unit box is the only one with a
+  ticket to the thing it has a ticket to, or let there be any number of
+  work-unit boxes out there that have a ticket to that thing, and, in either
+  case, can tell the scheduler person to control how many box-papers to a
+  Kept box it gives out before requiring one of them to return. \ For this
+  simple tutorial, just assume that the Kept box is the only one with a
+  ticket to the thing inside it, and that only a single box-paper for the
+  Kept box can be outstanding at a time.
+
+  \;
+
+  For parallelism, notice that a request waiting in the Keeper does not
+  occupy any workers, nor the scheduler. \ It's only when the requested Kept
+  gets sent along the response arrow that a new work-unit gets created, to
+  occupy a worker. \ Also, the scheduler person only spends time checking for
+  a box when the request comes in and when a box-paper for a Kept box enters
+  the Keeper. \ So, the workers and scheduler person are free to do other
+  things while the request for the Kept box sits in the Keeper, waiting for
+  the box-paper for the Kept box to come back into the Keeper.
+
+  When designing your own code, the more places you can make copies of a
+  box-paper and have it go down different paths on the work table, the
+  better! \ The trick will be putting in HoldUntils and ReJoiners to be sure
+  workers don't get the chance to do things in the wrong order, or to fight
+  over the same thing, trying to use it at the same time! \ The debugging
+  process will help with finding all the places you need to add HoldUnitls
+  and ReJoiners, so feel safe that if one's needed, you'll hear about it!
+
+  \;
+
+  That's it for this simple introduction to the WorkTable patterns, now get
+  one of the example programs, and keep this tutorial by your side to remind
+  you of what each of the BLIS_WT__... \ calls in the example program does.
+  \ Happy coding!\ 
+
+  \;
+</body>
+
+<\initial>
+  <\collection>
+    <associate|page-type|letter>
+  </collection>
+</initial>
+
+<\references>
+  <\collection>
+    <associate|auto-1|<tuple|1|1>>
+    <associate|auto-2|<tuple|2|2>>
+    <associate|auto-3|<tuple|3|2>>
+  </collection>
+</references>
+
+<\auxiliary>
+  <\collection>
+    <\associate|toc>
+      <with|par-left|<quote|6fn>|Hello, <datoms|<macro|x|<repeat|<arg|x>|<with|font-series|medium|<with|font-size|1|<space|0.2fn>.<space|0.2fn>>>>>|<htab|5mm>>
+      <no-break><pageref|auto-1><vspace|0.15fn>>
+
+      <with|par-left|<quote|6fn>|Let's work through an example
+      <datoms|<macro|x|<repeat|<arg|x>|<with|font-series|medium|<with|font-size|1|<space|0.2fn>.<space|0.2fn>>>>>|<htab|5mm>>
+      <no-break><pageref|auto-2><vspace|0.15fn>>
+
+      <with|par-left|<quote|6fn>|Not all piles are the same,
+      <datoms|<macro|x|<repeat|<arg|x>|<with|font-series|medium|<with|font-size|1|<space|0.2fn>.<space|0.2fn>>>>>|<htab|5mm>>
+      <no-break><pageref|auto-3><vspace|0.15fn>>
+    </associate>
+  </collection>
+</auxiliary>
\ No newline at end of file
diff -r 556a9b80cdb5 -r b793b4934cf8 0__Papers/Work_Table/WorkTable_tutorial/figures/Scheduling_states_2.eps
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/0__Papers/Work_Table/WorkTable_tutorial/figures/Scheduling_states_2.eps	Mon Apr 16 09:27:38 2012 -0700
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+count op_count sub {pop} repeat
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diff -r 556a9b80cdb5 -r b793b4934cf8 0__Papers/Work_Table/WorkTable_tutorial/latex/Sept_2011__WorkTable_tutorial.tex
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/0__Papers/Work_Table/WorkTable_tutorial/latex/Sept_2011__WorkTable_tutorial.tex	Mon Apr 16 09:27:38 2012 -0700
@@ -0,0 +1,1392 @@
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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/
+% Read the url.sty source comments for usage information. Basically,
+% \url{my_url_here}.
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+% *** Do not adjust lengths that control margins, column widths, etc. ***
+% *** 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{How to Write a Parallel Program Using the WorkTable Language}
+
+\author{Sean Halle}
+%\email{seanhalle@yahoo.com}
+\institute{OpenSource Stewardship Foundation}
+
+\maketitle             
+
+
+Hello, welcome to the tutorial for using the WorkTable language to create a parallel program. As an application programmer, your job is to make a system, that you can hand to a crew of workers.  They follow the instructions in your system, resulting in a completed job. The WorkTable language lets you make a system that any size of crew can use, to work together, keeping everyone busy, without making any mistakes. None of the workers has to think about anything, they just have to follow the instructions you wrote down on pieces of paper. 
+
+Okay, ready to start? The first thing you need to know to make your own system is what a bit of work looks like. In WorkTable, it’'s a list of instructions plus a box holding the stuff to perform the instructions on. A worker gets a list plus a box and follows the list on the contents of the box. At the
+end, the contents of the box has changed, the change is the work that was accomplished. 
+
+So, how to organize these bits of work? In WorkTable, to make organizing easier, instead of moving boxes around, we’ll put a number on each box, then write that number on a piece of paper and move the paper around.  Call the piece of paper a box-paper. The box-papers get put into piles.  Attached to each pile is a list of instructions to perform on the box contents. All the boxes in the pile get the same list of instructions done to them. The piles get laid out on a "Work Table", hence the name.  Arrows connect piles, indicating the flow of box-papers between piles. When the instructions from one pile have been completed on a box, its box-paper follows the arrow to a new pile.
+
+To do a unit of work, take a copy of the instructions, plus a box-paper, go get the box, then follow the
+instructions on the contents. We’ll call the list of instructions plus the box named by a box-paper a
+WorkUnit, and we’ll call the box containing the materials a WorkUnit Box.
+So, what’s inside a box? A WorkUnit Box (WUB) holds all the materials, plus notes from previous
+work done on those materials, like post-it notes to let later work-units know about things. Let’s say we’re
+writing a system for a team of workers to build a house. During construction, the parts of the house
+can’t actually be put into the box, so instead, a ticket representing ownership of the material is put into
+the box, like a ticket that owns “the south wall”. Only boxes that have a ticket for part of the house can
+do work on that part of the house.
+Let’s say, a box-paper lands in the “put in window” pile, the box will contain a ticket that owns a wall
+in the house, plus a ticket that owns one of the windows sitting in the storage lot. The reason for the
+tickets is to give us a way to make sure two workers don’t try to use the same material for two different
+bits of work at the same time! We’ll see more about keeping the workers out of each other’s hair soon.
+Great, now we have a box that holds all of the tickets for the materials used in the work, and we have
+piles that have the instructions for what to do on the materials, and we have a table to organize it all,
+how does the work actually happen?
+BLIS provides the table, and a person who sits at the table and does the moving the box-papers
+among the piles. We’ll call them the Scheduler Person, or just the Scheduler. A worker walks up to the
+table, and the Scheduler Person hands them a list of instructions plus a box-paper. The worker walks off,
+finds the box, and follows the instructions on the materials owned by the box. When done, they hand the
+box-paper back to the Scheduler person, who follows the arrows, puts the paper in a new pile, then picks
+another set of instructions plus box-paper and hands it to the worker, and so on. Because the Scheduler
+Person is part of the BLIS Work Table system, you, the programmer, don’t know what choices they will
+make, but you can tell them constraints on their choices, more on that later.
+That’s the basic idea of how a system is used. As a programmer, your task is to state the piles
+needed, draw the arrows between the piles, and write the instructions for each pile. When done, you’ll
+have a system for making the thing you want made, and any crew of workers will be able to show up and
+make one, no matter how many people they might have!
+1
+Let’s work through an example of making such a system for building a house. As a programmer,
+the first thing you write is the instructions that tell the scheduler person how to set up the table,
+including what piles to make, the arrows between the piles, and the instructions to put at each pile.
+When the program starts, these setup instructions run first. After the table is set up, the scheduler
+person starts picking box-papers from the piles and handing them to workers, with a copy of the pile-
+instructions, then getting box-papers back from the workers, following the arrows to put those into the
+appropriate piles, and repeating the picking and handing out, until the job is done.
+The instructions for how to set up the table is called the “setup” function. In setup, you’ll use built-in
+functions that start with “BLIS_WT__”, to tell the scheduler person the name and type of each pile
+(BLIS_WT__create_work_pile...), the pile-instructions (a standard C function), and the arrows
+between the piles (BLIS_WT__connect_pile_to_pile...).
+Like this:
+BLIS_WT__start_work_table_setup( WT_FOR_HOUSE_CONSTRUCTION );
+BLIS_WT__create_work_pile( FRAME_A_WALL, &make_the_frame_for_a_wall);
+BLIS_WT__create_work_pile( PUT_IN_WINDOW, &put_window_into_wall);
+BLIS_WT__create_work_pile(PUT_IN_DOOR, &put_door_into_wall);
+BLIS_WT__connect_pile_to_pile( ENTRY, FRAME_A_WALL);
+BLIS_WT__connect_pile_to_pile(FRAME_A_WALL, PUT_IN_WINDOW);
+BLIS_WT__connect_pile_to_pile(PUT_IN_WINDOW, PUT_IN_DOOR);
+BLIS_WT__end_work_table_setup( WT_FOR_HOUSE_CONSTRUCTION);
+When creating a pile, the first argument is the name of the pile, as an enum constant, the second is
+the pile-instructions, a pointer to a function. When connecting piles, the first argument is the name of
+the from-pile, the second the name of the to-pile. Notice, this work table arrangement only has paral-
+lelism for doing multiple walls at the same time. On a single wall, the work goes in-order, frame, then
+put in windows, then put in door. This shortcoming will be fixed with the new kinds of piles introduced
+next.
+Not all piles are the same, some are special, used only by the scheduler person, in effect to make sure
+no two workers interfere with each other, while still keeping all workers busy. For example, going back to
+installing a window, imagine that one of the workers took the window and tried to install it before the
+wall was finished! Or, that a worker painted the wall before the window was in, which would leave the
+window frame unpainted!
+To prevent these problems, there are piles called “hold until” – a box-paper is held in one of these piles
+until something happens that releases it. The instructions that go with a HoldUntil pile get performed by
+the scheduler person, and tell them, for a given box-paper that comes in, which releasing box-paper to
+watch for and where to watch for it (or them, because sometimes a held box-paper has multiple propen-
+dent box-papers).
+In this example, let’s say when a wall is done, that two box-papers are made for the WUB that owns
+it, one box-paper goes to a pile where all the windows get put into the wall, the other box-paper goes to
+the pile where the wall gets painted. If the second box-paper goes right in, it might get handed to a
+worker too early! It’s only when a box-paper leaves the “Install windows” pile, that the box-paper for the
+same box can leave the “hold until windows installed” pile and flow into the “paint” pile.
+One complication is that the scheduler person has to do some bookkeeping when watching for propen-
+dent box-papers. So for each spot that a HoldUntil might tell the scheduler person to watch, a Watcher
+is created, which causes a place to be setup for the scheduler person to keep track of which box-papers
+have passed that spot.
+Here’s what the setup code for such a HoldUntil would look like:
+BLIS_WT__create_Watcher_at_pile_exit(INSTALL_WINDOWS,INSTALL_WINDOWS_EXIT);
+BLIS_WT__create_HoldUntil_pile(HOLD_FOR_WINDOWS, &calc_ID_of_releasing_box);
+BLIS_WT__connect_pile_to_pile(HOLD_FOR_WINDOWS, PAINT_WALL);
+The first line creates a watcher – the first arg is the pile-exit to watch, the second is the watcher’s
+name. The second line creates the HoldUntil – the first argument is the name of the pile, the second is a
+pointer to a C function that calculates which WorkUnit Box is being waited upon, and where to watch for
+it. This function will use the name of the watcher that was created on the first line.
+Another kind of scheduler pile is called a ReJoiner. Sometimes, two different materials will have
+things done to them separately, but they have to join up again and be used together. For example, a
+door fits to a particular frame, the two get given to two different work unit boxes, and separately get
+sanded down, primed, and stained. When both are done, the door has to be joined back together with its
+frame, so a ReJoiner pile is made that matches the work-unit box that owns the door to the work-unit
+box that owns the frame. You, the programmer, write a function that takes a box and calculates
+a “match number” for it. The Scheduler Person sitting at the table will take the match_number function
+you write and use it to find pairs of work-unit-boxes. They put the pairs, together, onto the next pile.
+Continuing the example, to let doors and their frames be worked on separately, one of the piles has to
+separate them! The pile that does this will receive the door + frame as a unit, and has two choices on
+how to proceed – the first is to make two new work-unit-boxes and give one ownership of the door, the
+other ownership of the frame, then send those two along different arrows. The second is to make a copy
+of the piece of paper with the ID of the work-unit box, then send one copy down the path for doors and
+the other copy down the path for frames.
+The second option is less work, so try that. At the spot on the table where the two paths come back
+together, place a ReJoiner, which will have two inputs, one from each path. To each input attach a func-
+tion that just takes the ID of the work-unit-box and returns that as the match-ID. This will cause one
+copy of the paper with the work-unit-box ID to be matched with the other copy. This way, it’s certain
+that both the door and the frame have completed before doing any more work with them.
+Here’s the code:
+BLIS_WT__ (dispatch pile to two others – a sand door pile and a sand frame pile – then a ReJoiner
+pile)
+dispatch pile – takes “house materials”, outputs “doors”, “door-frames”, “windows”, “materials”
+BLIS_WT__(ReJoiner pile made with the make-match-ID function for each input
+(show function that extracts ID and returns as match_ID)
+The next scheduler pile is called a Keeper pile, which keeps around work-unit boxes that might be
+needed at some point. As an example, say one of the work-piles makes a special jig for cutting the holes
+in a door to install a door-knob. Some of the doors arrive with the door-knob already installed, so it’s
+not certain which doors will need the jig. A separate jig is made for each kind of door, and when com-
+plete, the jig flows into a Keeper. More precisely, a ticket for the jig is put into a work-unit box and the
+box-paper for that box flows into the Keeper-pile.
+We will need some way to steer box-papers, in this case either sending to the Keeper so a door-knob
+can be installed, or by-passing the door-knob-install process. Another kind of scheduler pile gets used for
+this, called a Steer-pile. The instructions for one of these tell the scheduler person which of many outputs
+to send a box-paper on. All work-piles have only a single output spot, so a Steer-pile is needed to steer a
+box-paper among many possible routes.
+Continuing the example, let’s say the box-paper for a door flows into a work-pile. The instructions
+say to check if the door has a knob installed. The worker looks, and this door is missing the knob, so the
+instructions tell the worker to write a post-it note saying the box needs a knob installed, and another
+post-it saying the type of door. The instructions say where to put these notes in the box.
+From there, the box-paper flows into a Steer-pile, where the instructions tell the scheduler person to
+look inside the work-unit box and find the post-it left there by the worker. If the note says the door
+needs a knob installed, it flows out the “need knob” output, otherwise it flows out the “has a knob” output.
+The “needs knob” output was connected to the request-pile of the Keeper that has the jigs, where the
+instructions say to get the post-it that has the kind of door written on it. The instructions then have a
+numbered list and tell the scheduler person to match the name on the post-it to a name in the list, then
+look at the list number. This number is the ID of the work-unit-box that owns the jig needed for that
+kind of door!
+At this point, the scheduler person goes and checks if the work-unit-box with that ID on it is sitting in
+the Keeper room. If not, they leave a note for themselves, which they’ll check when putting work-unit-
+boxes into the room. Either way, whenever the work-unit box is in the room, the scheduler person sees it
+and puts its box-paper together with the box-paper from the request-pile, and flows them out of the
+Keeper along the arrow leaving the Keeper’s “response” output. In this example, the pointed-to will to be
+the work-pile for installing a door-knob!
+When the door-knob installation is complete, the work-unit box that owns the jig gets sent back to the
+Keeper-pile. When it arrives, the scheduler person checks their notes whether any requests are waiting
+for that work-unit box.
+Notice that the scheduler person is the only one with access to the Keeper room, so the scheduler
+alone controls which request-response pairs have a box-paper for a box that’s in the Keeper room. The
+way the scheduler person keeps track of this requires more depth to explain, but the end-effect is that the
+scheduler can be told to control Kept boxes in a few different ways: ensure that the Kept work-unit box is
+the only one with a ticket to the thing it has a ticket to, or let there be any number of work-unit boxes
+out there that have a ticket to that thing, and, in either case, can tell the scheduler person to control how
+many box-papers to a Kept box it gives out before requiring one of them to return. For this simple tuto-
+rial, just assume that the Kept box is the only one with a ticket to the thing inside it, and that only a
+single box-paper for the Kept box can be outstanding at a time.
+For parallelism, notice that a request waiting in the Keeper does not occupy any workers, nor the
+scheduler. It’s only when the requested Kept gets sent along the response arrow that a new work-unit
+gets created, to occupy a worker. Also, the scheduler person only spends time checking for a box when
+the request comes in and when a box-paper for a Kept box enters the Keeper. So, the workers and sched-
+uler person are free to do other things while the request for the Kept box sits in the Keeper, waiting for
+the box-paper for the Kept box to come back into the Keeper.
+When designing your own code, the more places you can make copies of a box-paper and have it go
+down different paths on the work table, the better! The trick will be putting in HoldUntils and ReJoiners
+to be sure workers don’t get the chance to do things in the wrong order, or to fight over the same thing,
+trying to use it at the same time! The debugging process will help with finding all the places you need to
+add HoldUnitls and ReJoiners, so feel safe that if one’s needed, you’ll hear about it!
+That’s it for this simple introduction to the WorkTable patterns, now get one of the example pro-
+grams, and keep this tutorial by your side to remind you of what each of the BLIS_WT__... calls in the
+example program does. Happy coding!
+
+
+
+
+
+
+=======================================
+\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}
+ }