[Python-Dev] Re: Are we collecting benchmark results across machines (original) (raw)

Josiah Carlson jcarlson at uci.edu
Sat Jan 3 15:58:41 EST 2004

Another small set of pystone and parrotbench results...

Best of 7 runs on a standard windows build of Python on windows 2000: Processor P4 2.26ghz P4 Cel 1.7ghz P2 Cel 400mhz bus 533 mhz 400 mhz 66 mhz l2cache 512k 128k 128k memory 1G DualChan DDR333 256M DDR200 384M SDR66 2.2.2 Pystone ~25600 ~18500 ~6086 2.3.2 Pystone ~31800 ~6830 2.3.2 Parrot 16.06s 83.4s 2.3.2 Pys*Par 510708 569622

A few things to note: I don't have consistant access to the 1.7ghz celeron, which is why it didn't get any 2.3 tests.

The p2 celeron is a dual processor system. There does not seem to be an easy way to give a process one processor affinity on the command line. However, even inserting a pause into pystone in order to alter processor affinity does not seem to appreciably alter the pystone speed. This may suggest that Python has a working set so large that it doesn't fit into the 128k of L2 cache on either of the celerons. This is supported by the fact that based on the python 2.2.2 pystone results, the 2.26 P4 performs like a 2.35 ghz P4 celeron (256/185*1.7), which could be due to the larger cache, higher speed memory, or more likely both.

It is also likely that the P4s aren't as fast per clock as the P2 due to the heavy branch misprediction penalties that the architecture suffers from.

Strange thing: The 2.26 ghz P4 gains more in the Pystone benchmark from the 2.2.2 -> 2.3.2 transition than the celeron 400, 24% and 12% increases in Pystones respectively.

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