On Wed, Nov 4, 2009 at 5:54 PM, Collin Winter <collinw@[...].com>  wrote:
>  Do note that the --track_memory option to perf.py imposes some
>  overhead that interferes with the performance figures.

Thanks for the notice, without -m/--track_memory the deviation in
results is indeed much smaller.

>  I'd recommend
>  running the benchmarks again without --track_memory.

Done:

$ python unladen-tests/perf.py -r --benchmarks=-2to3,all py261/python wpy/python

Report on Linux zeus 2.6.31-14-generic #48-Ubuntu SMP Fri Oct 16
14:05:01 UTC 2009 x86_64
Total CPU cores: 2

ai:
Min: 0.629343 ->  0.576259: 9.21% faster
Avg: 0.634689 ->  0.581551: 9.14% faster
Significant (t=39.404870, a=0.95)
Stddev: 0.01259 ->  0.00484: 160.04% smaller


call_simple:
Min: 1.796710 ->  1.700046: 5.69% faster
Avg: 1.801533 ->  1.716367: 4.96% faster
Significant (t=137.452069, a=0.95)
Stddev: 0.00522 ->  0.00333: 56.64% smaller


django:
Min: 1.280840 ->  1.275350: 0.43% faster
Avg: 1.287179 ->  1.287233: 0.00% slower
Not significant
Stddev: 0.01055 ->  0.00581: 81.60% smaller


iterative_count:
Min: 0.211744 ->  0.123271: 71.77% faster
Avg: 0.213148 ->  0.128596: 65.75% faster
Significant (t=88.510311, a=0.95)
Stddev: 0.00233 ->  0.00926: 74.80% larger


normal_startup:
Min: 0.520829 ->  0.516412: 0.86% faster
Avg: 0.559170 ->  0.554678: 0.81% faster
Not significant
Stddev: 0.02031 ->  0.02093: 2.98% larger


pickle:
Min: 1.988127 ->  1.926643: 3.19% faster
Avg: 2.000676 ->  1.936185: 3.33% faster
Significant (t=36.712505, a=0.95)
Stddev: 0.01650 ->  0.00603: 173.67% smaller


pickle_dict:
Min: 1.681116 ->  1.619192: 3.82% faster
Avg: 1.701952 ->  1.629548: 4.44% faster
Significant (t=34.513963, a=0.95)
Stddev: 0.01721 ->  0.01200: 43.46% smaller


pickle_list:
Min: 0.918128 ->  0.884967: 3.75% faster
Avg: 0.925534 ->  0.891200: 3.85% faster
Significant (t=60.451407, a=0.95)
Stddev: 0.00496 ->  0.00276: 80.00% smaller


pybench:
Min: 58692 ->  51128: 14.79% faster
Avg: 59914 ->  52316: 14.52% faster

regex_compile:
Min: 0.894190 ->  0.816447: 9.52% faster
Avg: 0.900353 ->  0.826003: 9.00% faster
Significant (t=24.974080, a=0.95)
Stddev: 0.00448 ->  0.02943: 84.78% larger


regex_effbot:
Min: 0.124442 ->  0.123750: 0.56% faster
Avg: 0.134908 ->  0.126137: 6.95% faster
Significant (t=5.496357, a=0.95)
Stddev: 0.01581 ->  0.00218: 625.68% smaller


regex_v8:
Min: 0.132730 ->  0.143494: 7.50% slower
Avg: 0.134287 ->  0.147387: 8.89% slower
Significant (t=-40.654627, a=0.95)
Stddev: 0.00108 ->  0.00304: 64.34% larger


rietveld:
Min: 0.754050 ->  0.737335: 2.27% faster
Avg: 0.770227 ->  0.754642: 2.07% faster
Significant (t=7.547765, a=0.95)
Stddev: 0.01434 ->  0.01486: 3.49% larger


slowpickle:
Min: 0.858494 ->  0.795162: 7.96% faster
Avg: 0.862350 ->  0.799479: 7.86% faster
Significant (t=133.690989, a=0.95)
Stddev: 0.00394 ->  0.00257: 52.92% smaller


slowspitfire:
Min: 0.955587 ->  0.909843: 5.03% faster
Avg: 0.965960 ->  0.925845: 4.33% faster
Significant (t=16.351067, a=0.95)
Stddev: 0.01237 ->  0.02119: 41.63% larger


slowunpickle:
Min: 0.409312 ->  0.346982: 17.96% faster
Avg: 0.412381 ->  0.349148: 18.11% faster
Significant (t=242.889869, a=0.95)
Stddev: 0.00198 ->  0.00169: 17.61% smaller


startup_nosite:
Min: 0.195620 ->  0.194328: 0.66% faster
Avg: 0.230811 ->  0.238523: 3.23% slower
Significant (t=-3.869944, a=0.95)
Stddev: 0.01932 ->  0.02052: 5.87% larger


threaded_count:
Min: 0.222133 ->  0.133764: 66.06% faster
Avg: 0.236670 ->  0.147750: 60.18% faster
Significant (t=57.472693, a=0.95)
Stddev: 0.01317 ->  0.00813: 61.98% smaller


unpack_sequence:
Min: 0.000129 ->  0.000119: 8.43% faster
Avg: 0.000132 ->  0.000123: 7.22% faster
Significant (t=24.614061, a=0.95)
Stddev: 0.00003 ->  0.00011: 77.02% larger


unpickle:
Min: 1.191255 ->  1.149132: 3.67% faster
Avg: 1.218023 ->  1.162351: 4.79% faster
Significant (t=21.222711, a=0.95)
Stddev: 0.02242 ->  0.01362: 64.54% smaller


unpickle_list:
Min: 0.880991 ->  0.965611: 8.76% slower
Avg: 0.898949 ->  0.985231: 8.76% slower
Significant (t=-17.387537, a=0.95)
Stddev: 0.04838 ->  0.01103: 338.79% smaller
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