Mercurial > cgi-bin > hgwebdir.cgi > VMS > 2__runs_and_data
changeset 22:13a3ee4c9608
ucc visualization
| author | Nina Engelhardt <nengel@mailbox.tu-berlin.de> |
|---|---|
| date | Wed, 11 Apr 2012 15:18:24 +0200 |
| parents | 3092eb030708 |
| children | 8336ea9c3153 |
| files | scripts/ucc_and_loop_graph_treatment/column_view.py scripts/ucc_and_loop_graph_treatment/parse_loop_graph.py scripts/ucc_and_loop_graph_treatment/parse_ucc.py |
| diffstat | 3 files changed, 472 insertions(+), 192 deletions(-) [+] |
line diff
1.1 --- a/scripts/ucc_and_loop_graph_treatment/column_view.py Thu Mar 29 18:40:59 2012 +0200 1.2 +++ b/scripts/ucc_and_loop_graph_treatment/column_view.py Wed Apr 11 15:18:24 2012 +0200 1.3 @@ -8,7 +8,100 @@ 1.4 1.5 __num_idle = 0 #graph.node['start']['numcores'] * 2 1.6 1.7 -def fig_from_node(graph,node,num_cols,offset,positioning=None): 1.8 +### saving ### 1.9 + 1.10 +def save_computed_column_view(graph,num_cores,total_height,positioning,dependencies=None): 1.11 + vertical_scale_factor = 10000.0/float(total_height) 1.12 + __num_cols = 1 1.13 + f = sf.Fig(fig_nodes(graph,vertical_scale_factor,1,0,positioning)) 1.14 + if dependencies != None: 1.15 + f.d.append(draw_cross_core_deps(graph,num_cores,1,0,positioning,dependencies,vertical_scale_factor)) 1.16 + #f.trans = "x,{0}*y".format(10000.0/float(total_height)) 1.17 + w = __num_cols*__column_width*num_cores 1.18 + c = sf.canvas(f.SVG(),width="{0}px".format(w),height="10000px",viewBox='0 0 {0} 10000'.format(w)) 1.19 + c.save() 1.20 + 1.21 +def save_comparative_column_view(graph,num_cores,total_height,positioning=None): 1.22 + if positioning == None: 1.23 + num_cols = 2 1.24 + else: 1.25 + num_cols = 3 1.26 + vertical_scale_factor = 10000.0/float(total_height) 1.27 + f = sf.Fig() 1.28 + f.d.append(get_tsc_scale(graph,num_cores,num_cols,0)) 1.29 + f.d.append(fig_nodes(graph,num_cols,1,positioning=positioning)) 1.30 + if positioning!=None: 1.31 + f.d.append(fig_nodes(graph,num_cols,2)) 1.32 + w = __num_cols*__column_width*num_cores 1.33 + f.trans = "x,{0}*y".format(10000.0/float(total_height)) 1.34 + c = sf.canvas(f.SVG(),width="{0}px".format(w),height="10000px",viewBox='0 0 {0} 10000'.format(w)) 1.35 + c.save() 1.36 + 1.37 +def save_tsc_scale(graph,num_cores,total_height): 1.38 + nodes = get_tsc_scale(graph,num_cores,1,0,total_height) 1.39 + w = __column_width*num_cores 1.40 + c = sf.canvas(nodes.SVG(),width="{0}px".format(w),height="{0}px".format(10000),viewBox='0 0 {0} {1}'.format(w,10000)) 1.41 + c.save('tsc.svg') 1.42 + 1.43 + 1.44 + 1.45 +### drawing ### 1.46 + 1.47 +### timestamp counter ### 1.48 + 1.49 +def get_tsc_scale(graph,num_cores,num_cols,offset): 1.50 + nodes=sf.Fig() 1.51 + maxh = 0 1.52 + for node in graph: 1.53 + if node != 'start' and node != 'end': 1.54 + try: 1.55 + n , maxh = tsc_fig_from_node(graph,node,num_cols,offset,maxh) 1.56 + nodes.d.append(n) 1.57 + except Exception as e: 1.58 + print node,e 1.59 + #nodes.trans = "x,{0}*y".format(10000.0/float(total_height)) 1.60 + return nodes 1.61 + 1.62 +def tsc_fig_from_node(graph,node,num_cols,offset,maxh): 1.63 + tscstarttime = graph.node['start']['tscstarttime'] 1.64 + core = graph.node[node]['core'] 1.65 + x1 = num_cols * core * __column_width + offset * __column_width 1.66 + x2 = x1 + __node_width 1.67 + y1 = graph.node[node]['Timestamp_start'] - tscstarttime 1.68 + if graph.node[node].has_key('Timestamp_end'): 1.69 + y2 = graph.node[node]['Timestamp_end'] - tscstarttime 1.70 + else: 1.71 + y2 = y1 + graph.node[node]['weight'] 1.72 + if node[0]>=2*graph.node['start']['numcores']: 1.73 + f='yellow' 1.74 + else: 1.75 + f='gray' 1.76 + r = sf.Rect(x1,y1,x2,y2,fill=f) 1.77 + s = sf.Text((x1+x2)/2 , (y1+y2)/2 ,str(node),text_anchor="middle",font_size=20) 1.78 + try: 1.79 + if maxh < y2: 1.80 + maxh = y2 1.81 + except: 1.82 + pass 1.83 + return sf.Fig(r,s),maxh 1.84 + 1.85 + 1.86 + 1.87 +### calculated or annotated positioning ### 1.88 + 1.89 + 1.90 +def fig_nodes(graph,vertical_scale_factor,num_cols,offset,positioning=None): 1.91 + """Build all nodes.""" 1.92 + nodes = [] 1.93 + for node in graph: 1.94 + if node != 'start' and node != 'end': 1.95 + try: 1.96 + nodes.append(fig_from_node(graph,node,num_cols,offset,vertical_scale_factor,positioning)) 1.97 + except Exception as e: 1.98 + print node,e 1.99 + return sf.Fig(*nodes)#,trans="x,{0}*y".format(vertical_scale_factor)) 1.100 + 1.101 +def fig_from_node(graph,node,num_cols,offset,vertical_scale_factor,positioning=None): 1.102 """Build globally positioned node representation.""" 1.103 core = graph.node[node]['core'] 1.104 x1 = core * num_cols * __column_width + offset * __column_width 1.105 @@ -35,113 +128,44 @@ 1.106 f='red' 1.107 else: 1.108 f='gray' 1.109 - r = sf.Rect(x1,y1,x2,y2,fill=f,fill_opacity="40%") 1.110 - r2 = sf.Rect(x1,y1+graph.node[node]['work_offset'],x2,y1+graph.node[node]['work_offset']+graph.node[node]['Work_end']-graph.node[node]['Work_start'],fill=f, stroke_opacity=0) 1.111 - s = sf.Text((x1+x2)/2 , (y1+y2)/2 ,str(node),text_anchor="middle",font_size=20) 1.112 + r = sf.Rect(x1,y1* vertical_scale_factor,x2,y2* vertical_scale_factor,fill=f,fill_opacity="40%") 1.113 + r2 = sf.Rect(x1,(y1+graph.node[node]['work_offset'])* vertical_scale_factor,x2,(y1+graph.node[node]['work_offset']+graph.node[node]['Work_end']-graph.node[node]['Work_start'])* vertical_scale_factor,fill=f, stroke_opacity=0) 1.114 + s = sf.Text((x1+x2)/2 , (y1+y2)* vertical_scale_factor/2 ,str(node),text_anchor="middle",font_size=20) 1.115 if graph.node[node].has_key('AssignerInvocation_start') and graph.node[node].has_key('Assigner_start'): 1.116 h = graph.node[node]['Assigner_start'] - graph.node[node]['AssignerInvocation_start'] 1.117 - r1 = sf.Rect(x1,y1,x2,y1+h,fill='green',fill_opacity="70%") 1.118 + r1 = sf.Rect(x1,y1* vertical_scale_factor,x2,(y1+h)* vertical_scale_factor,fill='green',fill_opacity="70%") 1.119 return sf.Fig(r,r1,r2,s) 1.120 return sf.Fig(r,r2,s) 1.121 1.122 -def tsc_fig_from_node(graph,node,num_cols,offset,maxh): 1.123 - tscstarttime = graph.node['start']['tscstarttime'] 1.124 - core = graph.node[node]['core'] 1.125 - x1 = num_cols * core * __column_width + offset * __column_width 1.126 - x2 = x1 + __node_width 1.127 - y1 = graph.node[node]['Timestamp_start'] - tscstarttime 1.128 - if graph.node[node].has_key('Timestamp_end'): 1.129 - y2 = graph.node[node]['Timestamp_end'] - tscstarttime 1.130 - else: 1.131 - y2 = y1 + graph.node[node]['weight'] 1.132 - if node[0]>=2*graph.node['start']['numcores']: 1.133 - f='yellow' 1.134 - else: 1.135 - f='gray' 1.136 - r = sf.Rect(x1,y1,x2,y2,fill=f) 1.137 - s = sf.Text((x1+x2)/2 , (y1+y2)/2 ,str(node),text_anchor="middle") 1.138 - try: 1.139 - if maxh < y2: 1.140 - maxh = y2 1.141 - except: 1.142 - pass 1.143 - return sf.Fig(r,s),maxh 1.144 1.145 -def fig_nodes(graph,vertical_scale_factor,num_cols,offset,positioning=None): 1.146 - """Build all nodes.""" 1.147 - nodes = [] 1.148 - for node in graph: 1.149 - if node != 'start' and node != 'end': 1.150 - try: 1.151 - nodes.append(fig_from_node(graph,node,num_cols,offset,positioning=positioning)) 1.152 - except Exception as e: 1.153 - print node,e 1.154 - return sf.Fig(*nodes)#,trans="x,{0}*y".format(vertical_scale_factor)) 1.155 1.156 -def get_tsc_scale(graph,num_cores,num_cols,offset): 1.157 - nodes=sf.Fig() 1.158 - maxh = 0 1.159 - for node in graph: 1.160 - if node != 'start' and node != 'end': 1.161 - try: 1.162 - n , maxh = tsc_fig_from_node(graph,node,num_cols,offset,maxh) 1.163 - nodes.d.append(n) 1.164 - except Exception as e: 1.165 - print node,e 1.166 - #nodes.trans = "x,{0}*y".format(10000.0/float(total_height)) 1.167 - return nodes 1.168 +### dependencies ### 1.169 1.170 -def draw_dep(graph,num_cores,num_cols,offset,positioning,dep,color=(0,0,0)): 1.171 - a,b = dep 1.172 - core1 = graph.node[a]['core'] 1.173 - x1 = core1 * num_cols * __column_width + offset * __column_width + 0.5 * __column_width 1.174 - y1 = positioning[a] 1.175 - core2 = graph.node[b]['core'] 1.176 - x2 = core2 * num_cols * __column_width + offset * __column_width + 0.5 * __column_width 1.177 - y2 = positioning[b] - graph.node[b]['weight'] 1.178 - return sf.Line(x1,y1,x2,y2,style="stroke:rgb({},{},{});stroke-width:3".format(int(color[0]*255),int(color[1]*255),int(color[2]*255))) 1.179 - 1.180 - 1.181 -def draw_cross_core_deps(graph,num_cores,num_cols,offset,positioning,dependencies): 1.182 +def draw_cross_core_deps(graph,num_cores,num_cols,offset,positioning,dependencies,vertical_scale_factor): 1.183 f = sf.Fig() 1.184 hue = 0 1.185 hue_incr = 1.0/len(dependencies) 1.186 for depl in dependencies: 1.187 for a,b in depl: 1.188 if graph.node[a]['core'] != graph.node[b]['core']: 1.189 - f.d.append(draw_dep(graph,num_cores,num_cols,offset,positioning,(a,b),colorsys.hsv_to_rgb(hue,1,1))) 1.190 + f.d.append(draw_dep(graph,num_cores,num_cols,offset,positioning,(a,b),vertical_scale_factor,colorsys.hsv_to_rgb(hue,1,1))) 1.191 hue = hue + hue_incr 1.192 return f 1.193 1.194 -def save_comparative_column_view(graph,num_cores,total_height,positioning=None): 1.195 - if positioning == None: 1.196 - num_cols = 2 1.197 - else: 1.198 - num_cols = 3 1.199 - vertical_scale_factor = 10000.0/float(total_height) 1.200 - f = sf.Fig() 1.201 - f.d.append(get_tsc_scale(graph,num_cores,num_cols,0)) 1.202 - f.d.append(fig_nodes(graph,num_cols,1,positioning=positioning)) 1.203 - if positioning!=None: 1.204 - f.d.append(fig_nodes(graph,num_cols,2)) 1.205 - w = __num_cols*__column_width*num_cores 1.206 - f.trans = "x,{0}*y".format(10000.0/float(total_height)) 1.207 - c = sf.canvas(f.SVG(),width="{0}px".format(w),height="10000px",viewBox='0 0 {0} 10000'.format(w)) 1.208 - c.save() 1.209 +def draw_dep(graph,num_cores,num_cols,offset,positioning,dep,vertical_scale_factor,color=(0,0,0)): 1.210 + a,b = dep 1.211 + core1 = graph.node[a]['core'] 1.212 + x1 = core1 * num_cols * __column_width + offset * __column_width + 0.5 * __column_width 1.213 + y1 = positioning[a] * vertical_scale_factor 1.214 + core2 = graph.node[b]['core'] 1.215 + x2 = core2 * num_cols * __column_width + offset * __column_width + 0.5 * __column_width 1.216 + y2 = (positioning[b] - graph.node[b]['weight']) * vertical_scale_factor 1.217 + return sf.Line(x1,y1,x2,y2,style="stroke:rgb({0},{1},{2});stroke-width:3".format(int(color[0]*255),int(color[1]*255),int(color[2]*255))) 1.218 + 1.219 1.220 -def save_computed_column_view(graph,num_cores,total_height,positioning,dependencies=None): 1.221 - vertical_scale_factor = 10000.0/float(total_height) 1.222 - __num_cols = 1 1.223 - f = sf.Fig(fig_nodes(graph,vertical_scale_factor,1,0,positioning)) 1.224 - if dependencies != None: 1.225 - f.d.append(draw_cross_core_deps(graph,num_cores,1,0,positioning,dependencies)) 1.226 - f.trans = "x,{0}*y".format(10000.0/float(total_height)) 1.227 - w = __num_cols*__column_width*num_cores 1.228 - c = sf.canvas(f.SVG(),width="{0}px".format(w),height="10000px",viewBox='0 0 {0} 10000'.format(w)) 1.229 - c.save() 1.230 1.231 -def save_tsc_scale(graph,num_cores,total_height): 1.232 - nodes = get_tsc_scale(graph,num_cores,1,0,total_height) 1.233 - w = __column_width*num_cores 1.234 - c = sf.canvas(nodes.SVG(),width="{0}px".format(w),height="{0}px".format(10000),viewBox='0 0 {0} {1}'.format(w,10000)) 1.235 - c.save('tsc.svg') 1.236 + 1.237 + 1.238 + 1.239 + 1.240 +
2.1 --- a/scripts/ucc_and_loop_graph_treatment/parse_loop_graph.py Thu Mar 29 18:40:59 2012 +0200 2.2 +++ b/scripts/ucc_and_loop_graph_treatment/parse_loop_graph.py Wed Apr 11 15:18:24 2012 +0200 2.3 @@ -6,6 +6,84 @@ 2.4 import matplotlib.pyplot as plt 2.5 import column_view 2.6 2.7 +def main(): 2.8 + if len(sys.argv)<3: 2.9 + if len(sys.argv)==2: 2.10 + uccfile = open("LoopGraph.{0}".format(sys.argv[1])) 2.11 + counterfile = open("Counters.{0}.csv".format(sys.argv[1])) 2.12 + else: 2.13 + print "Usage: {} SCGfile Counterfile".format(sys.argv[0]) 2.14 + sys.exit() 2.15 + else: 2.16 + uccfile = open(sys.argv[1]) 2.17 + counterfile = open(sys.argv[2]) 2.18 + #print sys.getrecursionlimit() 2.19 + build_cg(uccfile,counterfile) 2.20 + 2.21 + 2.22 +def build_cg(loopfile,counterfile): 2.23 + d = read_from_file(loopfile) 2.24 + print "Parsed file", loopfile.name, "and found:" 2.25 + if d.has_key("unit"): 2.26 + print len(d["unit"]), "Units" 2.27 + if d.has_key("ctlDep"): 2.28 + print len(d["ctlDep"]), "Control Dependencies" 2.29 + if d.has_key("commDep"): 2.30 + print len(d["commDep"]), "Communication Dependencies" 2.31 + if d.has_key("dynDep"): 2.32 + print len(d["dynDep"]), "Dynamically chosen Dependencies" 2.33 + if d.has_key("hwDep"): 2.34 + print len(d["hwDep"]), "Hardware constraints" 2.35 + g = loopgraph_from_dict(d) 2.36 + add_attributes_to_nodes_from_file(g,counterfile) 2.37 + #cont = raw_input("Calculate and show critical path (y/N)? ") 2.38 + #if not cont.startswith(('y','Y')): 2.39 + # sys.exit() 2.40 + lend,predd = annotate_critical_path(g, 'start', 'end') 2.41 + print "Critical path length:",lend['end'] 2.42 + critical_path = get_path(predd,'end') 2.43 + if critical_path == None: 2.44 + print "No path found!" 2.45 + nx.draw(g) 2.46 + else: 2.47 + #print "Critical path:",critical_path 2.48 + print "Expected execution time:",path_length(g,critical_path),"cycles" 2.49 + try: 2.50 + actual_time = g.node['start']['tscendtime'] - g.node['start']['tscstarttime'] 2.51 + print "Actual execution time:", actual_time, "cycles" 2.52 + dif = actual_time - lend['end'] 2.53 + print "(Difference:", dif, "- Relative Error:", 100*float(dif)/float(lend['end']),"%)" 2.54 + print g.node['start']['starttimes'] 2.55 + print g.node['start']['tscstarttimes'] 2.56 + column_view.save_computed_column_view(g,g.node['start']['numcores'],max(actual_time,lend['end']),lend,[d["commDep"], d["dynDep"], d["ctlDep"]]) 2.57 + #column_view.save_tsc_scale(g,g.node['start']['numcores'],lend['end']) 2.58 + return # 2.59 + print "Node \tCalculated\t Actual\tCore\tDifference\tNon-cumulative part" 2.60 + drf = 0 2.61 + for n in critical_path: 2.62 + if g.node[n].has_key('AppResponder_end'): 2.63 + clen = g.node[n]['AppResponder_end'] 2.64 + elif g.node[n].has_key('AppResponder_start'): 2.65 + clen = g.node[n]['AppResponder_start'] 2.66 + else: 2.67 + print n 2.68 + if n!='start' and n!='end': 2.69 + print "{}\t{:10}\t{:10}\t({})\t{:10}\t{:10}".format(n,lend[n],clen,g.node[n]['core'],clen-lend[n],clen-lend[n]-drf) 2.70 + drf = clen-lend[n] 2.71 + except KeyError as e: 2.72 + print e 2.73 + return # 2.74 + colors = [] 2.75 + for node in g.nodes(): 2.76 + if node in critical_path: 2.77 + colors.append('r') 2.78 + else: 2.79 + colors.append('w') 2.80 + nx.draw(g, node_color=colors) 2.81 + plt.show() 2.82 + 2.83 + 2.84 + 2.85 def read_from_file(filename): 2.86 d = {} 2.87 reader = csv.reader(filename) 2.88 @@ -114,6 +192,8 @@ 2.89 g.node['start']['tscendtime']=max(tscendtimes.values()) 2.90 g.node['start']['numcores']=highestcore+1 2.91 2.92 + 2.93 + 2.94 def path_length(graph,path): 2.95 length = 0 2.96 if path==None: 2.97 @@ -145,6 +225,8 @@ 2.98 #print nl, ll 2.99 return longest 2.100 2.101 + 2.102 + 2.103 def annotate_critical_path(graph, start, end, lend={}, predd={}): 2.104 path_to_here = 0 2.105 if len(graph.predecessors(end)) == 0: 2.106 @@ -157,7 +239,7 @@ 2.107 path_to_here = lend[node] 2.108 predd[end] = node 2.109 except KeyError: 2.110 - print node, nlend 2.111 + print "Error in annotate_critical_path on node ", node 2.112 exit(0) 2.113 try: 2.114 lend[end] = path_to_here + graph.node[end]['weight'] 2.115 @@ -166,6 +248,10 @@ 2.116 exit(0) 2.117 return lend,predd 2.118 2.119 + 2.120 + 2.121 + 2.122 + 2.123 def get_path(predd,end): 2.124 path = [] 2.125 node = end 2.126 @@ -175,81 +261,6 @@ 2.127 path = [node] + path 2.128 return path 2.129 2.130 -def build_cg(loopfile,counterfile): 2.131 - d = read_from_file(loopfile) 2.132 - print "Parsed file", loopfile.name, "and found:" 2.133 - if d.has_key("unit"): 2.134 - print len(d["unit"]), "Units" 2.135 - if d.has_key("ctlDep"): 2.136 - print len(d["ctlDep"]), "Control Dependencies" 2.137 - if d.has_key("commDep"): 2.138 - print len(d["commDep"]), "Communication Dependencies" 2.139 - if d.has_key("dynDep"): 2.140 - print len(d["dynDep"]), "Dynamically chosen Dependencies" 2.141 - if d.has_key("hwDep"): 2.142 - print len(d["hwDep"]), "Hardware constraints" 2.143 - g = loopgraph_from_dict(d) 2.144 - add_attributes_to_nodes_from_file(g,counterfile) 2.145 - #cont = raw_input("Calculate and show critical path (y/N)? ") 2.146 - #if not cont.startswith(('y','Y')): 2.147 - # sys.exit() 2.148 - lend,predd = annotate_critical_path(g, 'start', 'end') 2.149 - print "Critical path length:",lend['end'] 2.150 - critical_path = get_path(predd,'end') 2.151 - if critical_path == None: 2.152 - print "No path found!" 2.153 - nx.draw(g) 2.154 - else: 2.155 - #print "Critical path:",critical_path 2.156 - print "Expected execution time:",path_length(g,critical_path),"cycles" 2.157 - try: 2.158 - actual_time = g.node['start']['tscendtime'] - g.node['start']['tscstarttime'] 2.159 - print "Actual execution time:", actual_time, "cycles" 2.160 - dif = actual_time - lend['end'] 2.161 - print "(Difference:", dif, "- Relative Error:", 100*float(dif)/float(lend['end']),"%)" 2.162 - print g.node['start']['starttimes'] 2.163 - print g.node['start']['tscstarttimes'] 2.164 - column_view.save_computed_column_view(g,g.node['start']['numcores'],max(actual_time,lend['end']),lend,[d["commDep"], d["dynDep"], d["ctlDep"]]) 2.165 - #column_view.save_tsc_scale(g,g.node['start']['numcores'],lend['end']) 2.166 - return # 2.167 - print "Node \tCalculated\t Actual\tCore\tDifference\tNon-cumulative part" 2.168 - drf = 0 2.169 - for n in critical_path: 2.170 - if g.node[n].has_key('AppResponder_end'): 2.171 - clen = g.node[n]['AppResponder_end'] 2.172 - elif g.node[n].has_key('AppResponder_start'): 2.173 - clen = g.node[n]['AppResponder_start'] 2.174 - else: 2.175 - print n 2.176 - if n!='start' and n!='end': 2.177 - print "{}\t{:10}\t{:10}\t({})\t{:10}\t{:10}".format(n,lend[n],clen,g.node[n]['core'],clen-lend[n],clen-lend[n]-drf) 2.178 - drf = clen-lend[n] 2.179 - except KeyError as e: 2.180 - print e 2.181 - return # 2.182 - colors = [] 2.183 - for node in g.nodes(): 2.184 - if node in critical_path: 2.185 - colors.append('r') 2.186 - else: 2.187 - colors.append('w') 2.188 - nx.draw(g, node_color=colors) 2.189 - plt.show() 2.190 - 2.191 - 2.192 -def main(): 2.193 - if len(sys.argv)<3: 2.194 - if len(sys.argv)==2: 2.195 - uccfile = open("LoopGraph.{0}".format(sys.argv[1])) 2.196 - counterfile = open("Counters.{0}.csv".format(sys.argv[1])) 2.197 - else: 2.198 - print "Usage: {} SCGfile Counterfile".format(sys.argv[0]) 2.199 - sys.exit() 2.200 - else: 2.201 - uccfile = open(sys.argv[1]) 2.202 - counterfile = open(sys.argv[2]) 2.203 - print sys.getrecursionlimit() 2.204 - build_cg(uccfile,counterfile) 2.205 2.206 2.207 if __name__ == "__main__":
3.1 --- a/scripts/ucc_and_loop_graph_treatment/parse_ucc.py Thu Mar 29 18:40:59 2012 +0200 3.2 +++ b/scripts/ucc_and_loop_graph_treatment/parse_ucc.py Wed Apr 11 15:18:24 2012 +0200 3.3 @@ -4,6 +4,41 @@ 3.4 import csv 3.5 import networkx as nx 3.6 import matplotlib.pyplot as plt 3.7 +import svgfig as sf 3.8 + 3.9 +aliases = {} 3.10 + 3.11 +def main(): 3.12 + sys.setrecursionlimit(10000) 3.13 + if len(sys.argv)<1: 3.14 + sys.exit() 3.15 + uccfile = open(sys.argv[1]) 3.16 + d = read_from_file(uccfile) 3.17 + g = uccgraph_from_dict(d) 3.18 + print "Parsed UCC from file", sys.argv[1], "and found:" 3.19 + if d.has_key("unit"): 3.20 + print len(d["unit"]), "Units" 3.21 + if d.has_key("ctlDep"): 3.22 + print len(d["ctlDep"]), "Control Dependencies" 3.23 + if d.has_key("commDep"): 3.24 + print len(d["commDep"]), "Communication Dependencies" 3.25 + if d.has_key("NtoN"): 3.26 + print len(d["NtoN"]), "N to N communicating groups" 3.27 + #print nx.simple_cycles(g) 3.28 + try: 3.29 + counterfile = open(sys.argv[2]) 3.30 + lend, rankd = rank_nodes_with_weight(g,'start','end', counterfile) 3.31 + save_ucc_with_weight(g, lend, rankd) 3.32 + except Exception as e: 3.33 + #raise 3.34 + print "Failed to process unit length information, generating no-length graph." 3.35 + lend,rankd = rank_nodes(g,'start','end') 3.36 + print "Highest rank =", lend['end'] 3.37 + save_ucc_as_svg(g,rankd) 3.38 + #nx.draw(g) 3.39 + #plt.show() 3.40 + 3.41 +########################## INPUT FNS ########################## 3.42 3.43 def read_from_file(filename): 3.44 d = {} 3.45 @@ -13,60 +48,270 @@ 3.46 if row[0] == "unit": 3.47 if not d.has_key("unit"): # not key in d: 3.48 d["unit"] = [] 3.49 - d["unit"].append( ( int(row[1]),int(row[2]) ) ) 3.50 + unit = ( int(row[1]),int(row[2]) ) 3.51 + #the following supposes that units appear in order, and that all units appear before any constraints. 3.52 + if not aliases.has_key(unit): 3.53 + d["unit"].append( unit ) 3.54 + aliases[unit]=unit 3.55 + if int(row[4]) == 1: 3.56 + aliases[unit[0],unit[1]+1]=aliases[unit] 3.57 if row[0] == "ctlDep": 3.58 if not d.has_key("ctlDep"): 3.59 d["ctlDep"] = [] 3.60 - d["ctlDep"].append( ( (int(row[1]),int(row[2])) , (int(row[3]),int(row[4])) ) ) 3.61 + node1 = aliases[(int(row[1]),int(row[2]))] 3.62 + node2 = aliases[(int(row[3]),int(row[4]))] 3.63 + if node1 != node2: 3.64 + d["ctlDep"].append( ( node1 , node2 ) ) 3.65 if row[0] == "commDep": 3.66 if not d.has_key("commDep"): 3.67 d["commDep"] = [] 3.68 - d["commDep"].append(( (int(row[1]),int(row[2])) , (int(row[3]),int(row[4])) )) 3.69 + node1 = aliases[(int(row[1]),int(row[2]))] 3.70 + node2 = aliases[(int(row[3]),int(row[4]))] 3.71 + if node1 != node2: 3.72 + d["commDep"].append(( node1 , node2 )) 3.73 if row[0] == "NtoN": 3.74 if not d.has_key("NtoN"): 3.75 d["NtoN"] = [] 3.76 n = int(row[1]) 3.77 senders = zip(map(int,row[2:2+2*n:2]),map(int,row[3:2+2*n:2])) 3.78 receivers = zip(map(int,row[2*n+2:4*n+2:2]),map(int,row[2*n+3:4*n+2:2])) 3.79 + asenders = list(set([aliases[s] for s in senders])) 3.80 + areceivers = list(set([aliases[s] for s in receivers])) 3.81 #print "Senders:",senders, "=",len(senders) 3.82 #print "Receivers:",receivers, "=",len(receivers) 3.83 - d["NtoN"].append((senders,receivers)) 3.84 + d["NtoN"].append((asenders,areceivers)) 3.85 except Exception as e: 3.86 print e 3.87 continue 3.88 return d 3.89 3.90 def uccgraph_from_dict(d): 3.91 - g = nx.Graph() 3.92 + g = nx.DiGraph() 3.93 + g.add_node("start") 3.94 + g.add_node("end") 3.95 g.add_nodes_from(d["unit"]) 3.96 g.add_edges_from(d["ctlDep"]) 3.97 g.add_edges_from(d["commDep"]) 3.98 - for senders,receivers in d["NtoN"]: 3.99 - g.add_node("NtoN0") 3.100 + for i,(senders,receivers) in enumerate(d["NtoN"]): 3.101 + g.add_node("NtoN"+str(i)) 3.102 for node in senders: 3.103 g.add_edge(node,"NtoN0") 3.104 for node in receivers: 3.105 g.add_edge("NtoN0",node) 3.106 + for node in g: 3.107 + if node != "start" and node != "end": 3.108 + if len(g.predecessors(node)) == 0: 3.109 + g.add_edge("start",node) 3.110 + if len(g.successors(node)) == 0: 3.111 + g.add_edge(node,"end") 3.112 return g 3.113 3.114 -def main(): 3.115 - if len(sys.argv)<1: 3.116 - sys.exit() 3.117 - uccfile = open(sys.argv[1]) 3.118 - d = read_from_file(uccfile) 3.119 - print "Parsed UCC from file", sys.argv[1], "and found:" 3.120 - if d.has_key("unit"): 3.121 - print len(d["unit"]), "Units" 3.122 - if d.has_key("ctlDep"): 3.123 - print len(d["ctlDep"]), "Control Dependencies" 3.124 - if d.has_key("commDep"): 3.125 - print len(d["commDep"]), "Communication Dependencies" 3.126 - if d.has_key("NtoN"): 3.127 - print len(d["NtoN"]), "N to N communicating groups" 3.128 - g = uccgraph_from_dict(d) 3.129 - nx.draw_spectral(g) 3.130 - plt.show() 3.131 +########################## NON-WEIGHTED UCC ########################## 3.132 3.133 +############ ranking ############ 3.134 + 3.135 +def rank_nodes(graph, start, end, lend={}, rankd={}): 3.136 + path_to_here = 0 3.137 + if len(graph.predecessors(end)) == 0: 3.138 + assert end == start 3.139 + for node in graph.predecessors(end): 3.140 + if not lend.has_key(node): 3.141 + lend,rankd = rank_nodes(graph, start, node, lend, rankd) 3.142 + try: 3.143 + if lend[node] > path_to_here: 3.144 + path_to_here = lend[node] 3.145 + except KeyError: 3.146 + print node 3.147 + exit(0) 3.148 + lend[end] = path_to_here + 1 3.149 + if rankd.has_key(lend[end]): 3.150 + rankd[lend[end]].append(end) 3.151 + else: 3.152 + rankd[lend[end]] = [end] 3.153 + return lend,rankd 3.154 + 3.155 +############ drawing ############ 3.156 + 3.157 +__rank_height = 100 3.158 +__index_width = 100 3.159 +__node_radius = 40 3.160 + 3.161 + 3.162 +def save_ucc_as_svg(graph,rankd): 3.163 + node_positions = {} 3.164 + nodes = draw_nodes(rankd,node_positions) 3.165 + edges = draw_edges(graph,node_positions) 3.166 + f = sf.Fig(nodes,edges) 3.167 + w = (max([len(r) for r in rankd.values()]) + 1) * __index_width 3.168 + h = (max(rankd.keys()) + 1) * __rank_height 3.169 + c = sf.canvas(f.SVG(),width="{0}px".format(w),height="{0}px".format(h),viewBox='0 0 {0} {1}'.format(w,h)) 3.170 + c.save("UCC.svg") 3.171 + 3.172 +def draw_nodes(rankd,node_positions): 3.173 + f = sf.Fig() 3.174 + for rank in rankd.keys(): 3.175 + for index, node in enumerate(rankd[rank]): 3.176 + f.d.append(draw_node(node,rank,index,node_positions)) 3.177 + return f 3.178 + 3.179 +def draw_node(node,rank,index,node_positions): 3.180 + cx = (index + 1)*__index_width 3.181 + cy = (rank + 1)*__rank_height 3.182 + node_positions[node] = (cx,cy) 3.183 + r = __node_radius 3.184 + c = sf.Ellipse(cx,cy,0,r,r,stroke='black',fill='yellow') 3.185 + t = sf.Text(cx,cy,str(node),font_size=20) 3.186 + return sf.Fig(c,t) 3.187 + 3.188 + 3.189 +def draw_edges(graph,node_positions): 3.190 + f = sf.Fig() 3.191 + for edge in nx.edges(graph): 3.192 + f.d.append(draw_edge(edge,node_positions)) 3.193 + return f 3.194 + 3.195 +def draw_edge(edge,node_positions): 3.196 + node1,node2 = edge 3.197 + x1,y1 = node_positions[node1] 3.198 + x2,y2 = node_positions[node2] 3.199 + return sf.Line(x1,y1,x2,y2,style="stroke:rgb(0,0,0);stroke-width:3") 3.200 + 3.201 + 3.202 + 3.203 + 3.204 +########################## WEIGHTED UCC ########################## 3.205 + 3.206 + 3.207 +############ ranking ############ 3.208 + 3.209 +def rank_nodes_with_weight(graph, start, end, filename): 3.210 + add_weights_to_nodes(graph, filename) 3.211 + return do_recursive_ranking(graph, start, end) 3.212 + 3.213 +def add_weights_to_nodes(g, filename): 3.214 + counterreader = (csv.reader)(filename,skipinitialspace=True) 3.215 + events = {} 3.216 + inversealiases = {} 3.217 + for row in counterreader: 3.218 + if row[0] == "event": 3.219 + n = (int(row[2]),int(row[3])) 3.220 + if not events.has_key(n): 3.221 + events[n]={} 3.222 + events[n][row[1]] = int(row[4]) 3.223 + if not inversealiases.has_key(aliases[n]): 3.224 + inversealiases[aliases[n]]=set() 3.225 + inversealiases[aliases[n]].add(n) 3.226 + for n in g: 3.227 + try: 3.228 + weight = 0 3.229 + if inversealiases.has_key(n): 3.230 + for a in inversealiases[n]: 3.231 + if events[n].has_key('Assigner_start') and events[n].has_key('AssignerInvocation_start'): 3.232 + weight += events[n]['Assigner_start'] - events[n]['AssignerInvocation_start'] 3.233 + if events[n].has_key('Assigner_end') and events[n].has_key('Assigner_start'): 3.234 + weight += events[n]['Assigner_end'] - events[n]['Assigner_start'] 3.235 + if events[n].has_key('Work_start') and events[n].has_key('Assigner_end'): 3.236 + weight += events[n]['Work_start'] - events[n]['Assigner_end'] 3.237 + if events[n].has_key('Work_end') and events[n].has_key('Work_start'): 3.238 + weight += events[n]['Work_end'] - events[n]['Work_start'] 3.239 + if events[n].has_key('AppResponderInvocation_start') and events[n].has_key('Work_end'): 3.240 + weight += events[n]['AppResponderInvocation_start'] - events[n]['Work_end'] 3.241 + if events[n].has_key('AppResponder_start') and events[n].has_key('AppResponderInvocation_start'): 3.242 + weight += events[n]['AppResponder_start'] - events[n]['AppResponderInvocation_start'] 3.243 + if events[n].has_key('AppResponder_end') and events[n].has_key('AppResponder_start'): 3.244 + weight += events[n]['AppResponder_end'] - events[n]['AppResponder_start'] 3.245 + if events[n].has_key('NextAssigner_start') and events[n].has_key('AppResponder_end'): 3.246 + weight += events[n]['NextAssigner_start'] - events[n]['AppResponder_end'] 3.247 + g.node[n]['weight'] = weight #+ weight/10 3.248 + except Exception as e: 3.249 + print n 3.250 + raise 3.251 + 3.252 + 3.253 +def do_recursive_ranking(graph, start, end, lend={}, rankd={}): 3.254 + path_to_here = 0 3.255 + if len(graph.predecessors(end)) == 0: 3.256 + assert end == start 3.257 + for node in graph.predecessors(end): 3.258 + if not lend.has_key(node): 3.259 + lend, rankd = do_recursive_ranking(graph, start, node, lend, rankd) 3.260 + try: 3.261 + if lend[node] > path_to_here: 3.262 + path_to_here = lend[node] 3.263 + except KeyError: 3.264 + print "Error in annotate_critical_path on node ", node 3.265 + exit(0) 3.266 + try: 3.267 + lend[end] = path_to_here + graph.node[end]['weight'] 3.268 + if rankd.has_key(path_to_here): 3.269 + rankd[path_to_here].append(end) 3.270 + else: 3.271 + rankd[path_to_here] = [end] 3.272 + except KeyError: 3.273 + print end, "has no attribute 'weight'" 3.274 + exit(0) 3.275 + return lend, rankd 3.276 + 3.277 + 3.278 +############ drawing ############ 3.279 + 3.280 +__column_width = 110 3.281 +__node_width = 100 3.282 + 3.283 +def save_ucc_with_weight(graph, lend, rankd): 3.284 + node_positions = {} 3.285 + scale_factor = 10000.0/float(lend['end']) 3.286 + nodes, max_cols = draw_nodes_with_weight(graph, lend, rankd, node_positions, scale_factor) 3.287 + edges = draw_edges_with_weight(graph,node_positions) 3.288 + f = sf.Fig(nodes,edges) 3.289 + #f.trans = "x,{0}*y".format(10000.0/float(lend['end'])) 3.290 + w = (max_cols +1) * __column_width 3.291 + h = 10000 3.292 + c = sf.canvas(f.SVG(),width="{0}px".format(w),height="{0}px".format(h),viewBox='0 0 {0} {1}'.format(w,h)) 3.293 + c.save("UCC.svg") 3.294 + 3.295 +def draw_nodes_with_weight(graph, lend, rankd, node_positions, scale_factor=1.0): 3.296 + f = sf.Fig() 3.297 + columnoccupancy = {} 3.298 + for rank in sorted(rankd.keys()): 3.299 + for node in rankd[rank]: 3.300 + f.d.append(draw_node_with_weight(graph, node, lend, rankd, columnoccupancy, node_positions, scale_factor)) 3.301 + return f, max(columnoccupancy.keys()) 3.302 + 3.303 +def draw_node_with_weight(graph, node, lend, rankd, columnoccupancy, node_positions, scale_factor=1.0): 3.304 + node_end = lend[node] 3.305 + node_start = node_end - graph.node[node]['weight'] 3.306 + column = 0 3.307 + while columnoccupancy.has_key(column) and columnoccupancy[column] > node_start: 3.308 + column = column + 1 3.309 + columnoccupancy[column] = node_end 3.310 + x1 = column * __column_width 3.311 + y1 = node_start*scale_factor 3.312 + x2 = x1 + __node_width 3.313 + y2 = node_end*scale_factor 3.314 + if y1 == y2: 3.315 + y2 = y1+1 3.316 + node_positions[node] = (x1,y1,x2,y2) 3.317 + r = sf.Rect(x1,y1,x2,y2,stroke='black',fill='yellow') 3.318 + t = sf.Text((x1+x2)/2.0 , (y1+y2)/2.0 ,str(node),text_anchor="middle",font_size=20) 3.319 + return sf.Fig(r,t) 3.320 + 3.321 +def draw_edges_with_weight(graph,node_positions): 3.322 + f = sf.Fig() 3.323 + for edge in nx.edges(graph): 3.324 + f.d.append(draw_edge_with_weight(edge,node_positions)) 3.325 + return f 3.326 + 3.327 +def draw_edge_with_weight(edge,node_positions): 3.328 + node1,node2 = edge 3.329 + x1_1,y1_1,x2_1,y2_1 = node_positions[node1] 3.330 + x1_2,y1_2,x2_2,y2_2 = node_positions[node2] 3.331 + m1 = (x1_1 + x2_1) / 2 3.332 + m2 = (x1_2 + x2_2) / 2 3.333 + return sf.Line(m1,y2_1,m2,y1_2,style="stroke:rgb(0,0,0);stroke-width:3") 3.334 + 3.335 + 3.336 +########################## 3.337 3.338 if __name__ == "__main__": 3.339 main()