IronPython Performance Report

An automated, lightweight comparison between 'IronPython 2.6' and 'Python26'
on 11/19/2009 12:25:30.

Machine Setup

• PC
  • Manufacturer - Dell Computer Corporation
  • Model - PowerEdge 860
  • Name - MERLIN-14
• Software
  • Operating System - Microsoft Windows NT 6.0.6002 Service Pack 2
  • CLR Version - 2.0.50727.4200
• CPU
  • Full Name - Intel(R) Pentium(R) D CPU 2.80GHz
  • Speed - 2800
  • Number of Cores - 2
• RAM - 2146070528
• Disk Drive - WDC WD1600JS-75NCB3 ATA Device

HelloWorld

Background
HelloWorld is a typical hello world program we've written and is used to evaluate
the startup time of a Python interpreter. Lower startup times indicate better
performance.

Notes:

• No command-line flags are passed to the Python interpreters

Results
Best Python26 HelloWorld run (out of 5 attempts): 0.0655611 seconds
Best IronPython 2.6 HelloWorld run (out of 5 attempts): 2.1076478 seconds

PyStone 1.1

Background
PyStone is an extremely high-level benchmark distributed with CPython. In
short, running pystone.py under various implementations of Python will emit
the number of PyStones (i.e., iterations) per second that can be run on a given
machine. A higher PyStone result indicates better overall performance of a Python
interpreter. The latest copy of PyStone can be found in lib\test\pystone.py
(relative to CPython installation locations).

Notes:

• By default pystone.py runs 50,000 passes to determine PyStones per second. The results below were generated using this default
• Due to site caching in the Dynamic Language Runtime, IronPython performs better with more PyStone passes than the default value

Results
Best Python26 PyStone run (out of 5 attempts): 39239.6 PyStones/second
Best IronPython 2.6 PyStone run (out of 5 attempts): 55765.7 PyStones/second

PyBench 2.0

Background
PyBench is a collection of low-level benchmarks distributed with CPython. Whereas
PyStone can be used to discover the overall performance of the Python interpreter,
PyBench targets specific areas (e.g., the amount of time it takes to concatenate
two strings). You can find the latest version of PyBench on CPython's Subversion
source control system (e.g., http://svn.python.org/projects/python/trunk/Tools/pybench/).

Please note the following:

• Much of the platform module is broken under IPy. As such, build numbers, build dates, etc had to be faked under IPy
• The IPy garbage collector cannot be disabled. Although this puts IPy at a disadvantage, we kept it turned off for the CPy run
• sys.setcheckinterval does not function properly under IronPython. This is another optimization CPython gets that IronPython doesn't.
• 1 rounds and a warp factor of 1 were used.

Results
(this=C:\SnapTemp\IronPython 2.6, other=C:\SnapTemp\Python26)

Test	min run-time this	min run-time other	min run-time diff	avg run-time this	avg run-time other	avg run-time diff
BuiltinFunctionCalls:	403ms	1737ms	-76.8%	403ms	1737ms	-76.8%
BuiltinMethodLookup:	606ms	1835ms	-67.0%	606ms	1835ms	-67.0%
CompareFloats:	28ms	1075ms	-97.4%	28ms	1075ms	-97.4%
CompareFloatsIntegers:	403ms	1354ms	-70.2%	403ms	1354ms	-70.2%
CompareIntegers:	27ms	853ms	-96.9%	27ms	853ms	-96.9%
CompareInternedStrings:	395ms	1237ms	-68.1%	395ms	1237ms	-68.1%
CompareLongs:	29ms	1071ms	-97.3%	29ms	1071ms	-97.3%
CompareStrings:	477ms	1428ms	-66.6%	477ms	1428ms	-66.6%
CompareUnicode:	400ms	1188ms	-66.3%	400ms	1188ms	-66.3%
ComplexPythonFunctionCalls:	2149ms	2574ms	-16.5%	2149ms	2574ms	-16.5%
ConcatStrings:	5129ms	3004ms	70.7%	5129ms	3004ms	70.7%
ConcatUnicode:	3040ms	2602ms	16.8%	3040ms	2602ms	16.8%
CreateInstances:	839ms	2035ms	-58.8%	839ms	2035ms	-58.8%
CreateNewInstances:	1121ms	1552ms	-27.8%	1121ms	1552ms	-27.8%
CreateStringsWithConcat:	2880ms	1113ms	158.8%	2880ms	1113ms	158.8%
CreateUnicodeWithConcat:	809ms	1250ms	-35.3%	809ms	1250ms	-35.3%
DictCreation:	2276ms	1052ms	116.3%	2276ms	1052ms	116.3%
DictWithFloatKeys:	2070ms	2956ms	-30.0%	2070ms	2956ms	-30.0%
DictWithIntegerKeys:	1818ms	851ms	113.8%	1818ms	851ms	113.8%
DictWithStringKeys:	1990ms	1043ms	90.7%	1990ms	1043ms	90.7%
ForLoops:	562ms	658ms	-14.6%	562ms	658ms	-14.6%
IfThenElse:	291ms	838ms	-65.3%	291ms	838ms	-65.3%
ListSlicing:	3713ms	1493ms	148.7%	3713ms	1493ms	148.7%
NestedForLoops:	640ms	1054ms	-39.3%	640ms	1054ms	-39.3%
NormalClassAttribute:	2961ms	1124ms	163.4%	2961ms	1124ms	163.4%
NormalInstanceAttribute:	3710ms	1030ms	260.3%	3710ms	1030ms	260.3%
PythonFunctionCalls:	325ms	1647ms	-80.3%	325ms	1647ms	-80.3%
PythonMethodCalls:	3556ms	1866ms	90.6%	3556ms	1866ms	90.6%
Recursion:	559ms	2214ms	-74.8%	559ms	2214ms	-74.8%
SecondImport:	966ms	1248ms	-22.6%	966ms	1248ms	-22.6%
SecondPackageImport:	1059ms	1313ms	-19.3%	1059ms	1313ms	-19.3%
SecondSubmoduleImport:	1496ms	1724ms	-13.2%	1496ms	1724ms	-13.2%
SimpleComplexArithmetic:	605ms	1324ms	-54.3%	605ms	1324ms	-54.3%
SimpleDictManipulation:	2072ms	1094ms	89.4%	2072ms	1094ms	89.4%
SimpleFloatArithmetic:	495ms	1475ms	-66.4%	495ms	1475ms	-66.4%
SimpleIntFloatArithmetic:	558ms	760ms	-26.6%	558ms	760ms	-26.6%
SimpleIntegerArithmetic:	542ms	757ms	-28.4%	542ms	757ms	-28.4%
SimpleListManipulation:	1384ms	911ms	51.9%	1384ms	911ms	51.9%
SimpleLongArithmetic:	1075ms	1197ms	-10.2%	1075ms	1197ms	-10.2%
SmallLists:	1464ms	1623ms	-9.8%	1464ms	1623ms	-9.8%
SmallTuples:	871ms	1429ms	-39.1%	871ms	1429ms	-39.1%
SpecialClassAttribute:	3210ms	1103ms	190.9%	3210ms	1103ms	190.9%
SpecialInstanceAttribute:	3865ms	1198ms	222.7%	3865ms	1198ms	222.7%
StringMappings:	3055ms	2353ms	29.8%	3055ms	2353ms	29.8%
StringPredicates:	1346ms	1798ms	-25.1%	1346ms	1798ms	-25.1%
StringSlicing:	1414ms	1522ms	-7.1%	1414ms	1522ms	-7.1%
TryExcept:	260ms	573ms	-54.6%	260ms	573ms	-54.6%
TryFinally:	949ms	1808ms	-47.5%	949ms	1808ms	-47.5%
TryRaiseExcept:	63930ms	1083ms	5805.3%	63930ms	1083ms	5805.3%
TupleSlicing:	2090ms	1517ms	37.8%	2090ms	1517ms	37.8%
UnicodeMappings:	2059ms	949ms	117.0%	2059ms	949ms	117.0%
UnicodePredicates:	1391ms	1297ms	7.2%	1391ms	1297ms	7.2%
UnicodeSlicing:	1399ms	1737ms	-19.5%	1399ms	1737ms	-19.5%
WithFinally:	652ms	2199ms	-70.4%	652ms	2199ms	-70.4%
WithRaiseExcept:	71699ms	1681ms	4164.4%	71699ms	1681ms	4164.4%
Totals:	213113ms	79407ms	168.4%	213113ms	79407ms	168.4%

Richards

Background
Much like PyStone, richards.py is a high-level benchmark intended to give the
Python user a single result indicating the overall "goodness" factor of a Python
interpreter. This benchmark is distributed with the PyPy interpreter, although
the original version was written in BCPL by Dr. Martin Richards at Cambridge
University. Lower "Average time per iteration" results indicate better performance.

Results
Best average time per iteration for Python26 (out of 5 attempts): 611.8
Best average time per iteration for IronPython 2.6 (out of 5 attempts): 1400.05