contrib/cortex-strings/scripts/plot-sizes.py

   1 #!/usr/bin/env python
   2
   3 """Plot the performance for different block sizes of one function across
   4 variants.
   5 """
   6
   7 import libplot
   8
   9 import pylab
  10 import pdb
  11 import math
  12
  13 def pretty_kb(v):
  14     if v < 1024:
  15         return '%d' % v
  16     else:
  17         if v % 1024 == 0:
  18             return '%d k' % (v//1024)
  19         else:
  20             return '%.1f k' % (v/1024)
  21
  22 def plot(records, function, alignment=None, scale=1):
  23     variants = libplot.unique(records, 'variant', prefer='this')
  24     records = [x for x in records if x.function==function]
  25
  26     if alignment != None:
  27         records = [x for x in records if x.src_alignment==alignment[0] and
  28                    x.dst_alignment==alignment[1]]
  29
  30     alignments = libplot.unique(records, ('src_alignment', 'dst_alignment'))
  31     if len(alignments) != 1:
  32         return False
  33     if libplot.alignments_equal(alignments):
  34         aalignment = alignments[0][0]
  35     else:
  36         aalignment = "%s:%s" % (alignments[0][0], alignments[0][1])
  37
  38     bytes = libplot.unique(records, 'bytes')[0]
  39
  40     colours = libplot.make_colours()
  41     all_x = []
  42
  43     pylab.figure(1).set_size_inches((6.4*scale, 4.8*scale))
  44     pylab.clf()
  45
  46     if 'str' in function:
  47         # The harness fills out to 16k.  Anything past that is an
  48         # early match
  49         top = 16384
  50     else:
  51         top = 2**31
  52
  53     for variant in variants:
  54         matches = [x for x in records if x.variant==variant and x.bytes <= top]
  55         matches.sort(key=lambda x: x.bytes)
  56
  57         X = sorted(list(set([x.bytes for x in matches])))
  58         Y = []
  59         Yerr = []
  60         for xbytes in X:
  61             vals = [x.bytes*x.loops/x.elapsed/(1024*1024) for x in matches if x.bytes == xbytes]
  62             if len(vals) > 1:
  63                 mean = sum(vals)/len(vals)
  64                 Y.append(mean)
  65                 if len(Yerr) == 0:
  66                     Yerr = [[], []]
  67                 err1 = max(vals) - mean
  68                 assert err1 >= 0
  69                 err2 = min(vals) - mean
  70                 assert err2 <= 0
  71                 Yerr[0].append(abs(err2))
  72                 Yerr[1].append(err1)
  73             else:
  74                 Y.append(vals[0])
  75
  76         all_x.extend(X)
  77         colour = colours.next()
  78
  79         if X:
  80             pylab.plot(X, Y, c=colour)
  81             if len(Yerr) > 0:
  82                 pylab.errorbar(X, Y, yerr=Yerr, c=colour, label=variant, fmt='o')
  83             else:
  84                 pylab.scatter(X, Y, c=colour, label=variant, edgecolors='none')
  85
  86     pylab.legend(loc='upper left', ncol=3, prop={'size': 'small'})
  87     pylab.grid()
  88     pylab.title('%(function)s of %(aalignment)s byte aligned blocks' % locals())
  89     pylab.xlabel('Size (B)')
  90     pylab.ylabel('Rate (MB/s)')
  91
  92     # Figure out how high the range goes
  93     top = max(all_x)
  94
  95     power = int(round(math.log(max(all_x)) / math.log(2)))
  96
  97     pylab.semilogx()
  98
  99     pylab.axes().set_xticks([2**x for x in range(0, power+1)])
 100     pylab.axes().set_xticklabels([pretty_kb(2**x) for x in range(0, power+1)])
 101     pylab.xlim(0, top)
 102     pylab.ylim(0, pylab.ylim()[1])
 103     return True
 104
 105 def main():
 106     records = libplot.parse()
 107
 108     functions = libplot.unique(records, 'function')
 109     alignments = libplot.unique(records, ('src_alignment', 'dst_alignment'))
 110
 111     for function in functions:
 112         for alignment in alignments:
 113             for scale in [1, 2.5]:
 114                 if plot(records, function, alignment, scale):
 115                     pylab.savefig('sizes-%s-%02d-%02d-%.1f.png' % (function, alignment[0], alignment[1], scale), dpi=72)
 116
 117     pylab.show()
 118
 119 if __name__ == '__main__':
 120     main()