1 files changed, 171 insertions, 0 deletions
diff --git a/benchmarks/CUDA/MUM/make_figures.py b/benchmarks/CUDA/MUM/make_figures.py
new file mode 100644
index 0000000..efc0f33
--- /dev/null
+++ b/benchmarks/CUDA/MUM/make_figures.py
@@ -0,0 +1,171 @@
+#!/fs/sz-user-supported/Linux-i686/bin/python2.5
+import matplotlib
+matplotlib.use('PS')
+
+import pylab
+import csv
+
+def get_stats(filename):
+	stats = {}
+	statfile = open(filename)
+	stats = dict([(key, float(value)) for (key, value) in csv.reader(statfile)])
+	return stats
+
+from pylab import arange,pi,sin,cos,sqrt
+
+def set_figure_props():
+	fig_width_pt = 225.0  # Get this from LaTeX using \showthe\columnwidth
+	inches_per_pt = 1.0/72.27               # Convert pt to inch
+	golden_mean = (sqrt(5)-1.0)/2.0         # Aesthetic ratio
+	fig_width = fig_width_pt*inches_per_pt  # width in inches
+	fig_height = 1.5*fig_width*golden_mean      # height in inches
+	fig_size =  [fig_width,fig_height]
+	params = {'backend': 'ps',
+			  'axes.labelsize': 8,
+			  'axes.linewidth': 0.5,
+			  'text.fontsize': 8,
+			  'xtick.labelsize': 7,
+			  'ytick.labelsize': 7,
+			  'legend.fontsize': 7,
+			  'legend.linewidth':0.5,
+			  'title.fontsize' : 8,
+			  'text.usetex': True,
+			  'figure.figsize': fig_size}
+	pylab.rcParams.update(params)
+
+def draw_speedup_figures(outfile, fig_title):
+	query_lens = []
+	app_speedups = []
+	kernel_speedups = []
+	f = open(outfile)
+	headers = f.next()
+	headers = headers.strip()
+	headers = headers.split(',')
+	
+	query_col = headers.index("QUERY")
+	kernel_col = headers.index("KERNEL_SPEEDUP")
+	mummer_speed_col = headers.index("MUMMER_SPEEDUP")
+	
+	for vals in csv.reader(f, 'excel', delimiter=' '):
+		query_lens.append(int(vals[query_col]))
+		app_speedups.append(float(vals[mummer_speed_col]))
+		kernel_speedups.append(float(vals[kernel_col]))
+		
+	draw_speedup_fig(query_lens,
+					 kernel_speedups,
+					 fig_title,
+					 outfile + ".kernel_speedup.eps")
+
+def draw_speedup_fig(x, y, fig_title, filename):
+	set_figure_props()
+	ax = pylab.subplot(111)
+	
+	pylab.semilogx(x, y, linestyle=':', marker='v', basex=2)
+
+	pylab.xticks(x)
+	frm = pylab.FormatStrFormatter("%d")
+	ax.xaxis.set_major_formatter(frm)
+
+	ax.xaxis.grid(True, which="minor")
+	pylab.xlabel("Query length (bp - log scale)")
+	pylab.ylabel("Speedup")
+	pylab.title(fig_title, fontsize=9)
+
+	pylab.savefig(filename)
+	pylab.close()
+	
+def make_time_breakout():
+	statfiles = ["cbriggsae/cleanreads.fna-100.gpustats",
+				 "lmonocytogenes/cleanreads.fna-20.gpustats",
+				 "s_suis/cleanreads.fna-20.gpustats"
+				 ]
+	
+	labels = [ "\emph{C. briggsae}",
+			   "\emph{L. monocytogenes}",
+			  "\emph{S. suis} "
+			  ]
+	
+	stats = {}
+	convert_to_seconds = ["Total",
+						  "Kernel",
+						  "Print matches",
+						  "Copy queries to GPU",
+						  "Copy output from GPU",
+						  "Copy suffix tree to GPU",
+						  "Read queries from disk",
+						  "Suffix tree constructions"]
+	
+	for f in statfiles:
+		f_stats = get_stats(f)
+		for (key, value) in f_stats.iteritems():
+			
+			if key in convert_to_seconds:
+				val = value / 1000.0 #float( value/f_stats["TOTAL"]
+			else:
+				val = int(value)
+			if key in stats:
+				stats[key].append(val)
+			else:
+				stats[key] = [val]			
+	
+	ind = arange(0,3.6,1.2 )    # the x locations for the groups
+
+	width = 0.35       # the width of the bars: can also be len(x) sequence
+	
+	i = 0	
+## colors = [ "#e31a1c",
+## 		   "#377db8",
+## 		   "#4daf4a",
+## 		   "#984ea3",
+## 		   "#ffff33",
+## 		   "#ff7f00"]
+	
+	colors = [ "#FF4500",
+			   "#1E90FF",
+			   "#90EE90",
+			   "#FFD700",
+			   "#DA70D6",
+			   "#D2B48C"]
+
+	set_figure_props()
+	pylab.subplot(111)
+	transfer = []
+	for j in range(0, len(statfiles)):
+		transfer.append( stats["Copy suffix tree to GPU"][j] + stats["Copy output from GPU"][j] + stats["Copy queries to GPU"][j])
+
+	stats["Data transfer to GPU"] = transfer
+	
+	del stats["Copy suffix tree to GPU"]
+	del stats["Copy output from GPU"]
+	del stats["Copy queries to GPU"]
+
+	del stats["Total"]
+	
+	lengths = stats["Minimum substring length"]
+	
+	del stats["Minimum substring length"]
+	del stats["Average query length"]
+
+
+	plots = []
+	running_totals = [0 for j in range(0,len(statfiles))]
+	for (category, series) in stats.iteritems():
+		plots.append(pylab.bar(ind, series, width, color=colors[i], bottom=running_totals))
+		running_totals = [running_totals[j] + series[j] for j in range(0, len(series))]
+		i += 1
+	
+	#pylab.xticks(ind+width/2., labels )
+	pylab.xticks(ind +width/2., labels )
+	
+
+	pylab.title("Time spent by phase in MUMmerGPU", fontsize=9)
+	pylab.ylabel("time (s)")
+	pylab.xlim(-width,len(ind))
+	pylab.ylim(0, 600)
+	pylab.legend( [p[0] for p in reversed(plots)], [key for key in reversed(stats.keys())] )
+	
+	pylab.savefig('time_breakout.eps')
+	pylab.close()
+
+make_time_breakout()
+draw_speedup_figures("anthrax/speedup.out", "Kernel speedup, GPU vs. CPU")