Re: [Numpy-discussion] debian benchmarks
A Monday 05 July 2010 15:32:51 Isaac Gouy escrigué: Sturla Molden sturla at molden.no writes: It is also the kind of tasks where NumPy would help. It would be nice to get NumPy into the shootout. At least for the sake of advertising http://shootout.alioth.debian.org/u32/program.php?test=spectralnormlang=py thonid=2 Let's join the game :-) If I run the above version on my desktop computer (Intel E8600 Duo @ 3 GHz, DDR2 @ 800 MHz memory) I get: $ time python -OO spectralnorm-numpy.py 5500 1.274224153 real0m9.724s user0m9.295s sys 0m0.269s which should correspond to the 12.86s in shootout (so my machine is around 30% faster). But, if I use ATLAS (3.9.25) so as to accelerate linear algebra: $ python -OO spectralnorm-numpy.py 5500 1.274224153 real0m5.862s user0m5.566s sys 0m0.225s Then, my profile said that building M matrix took a lot of time. After using numexpr to improve this (see attached script), I get: $ python -OO spectralnorm-numpy-numexpr.py 5500 1.274224153 real0m3.333s user0m3.071s sys 0m0.163s Interestingly, memory consumption also dropped from 480 MB to 255 MB. Finally, if using Intel's MKL for taking advantage of my 2 cores: $ python -OO spectralnorm-numpy-numexpr.py 5500 1.274224153 real0m2.785s user0m4.117s sys 0m0.139s which is a 3.5x improvement over the initial version. Also, this seems faster (around ~25%), and consumes similar memory than the fastest version written in pure C in interesting alternatives section: http://shootout.alioth.debian.org/u32/performance.php?test=spectralnorm#about I suppose that, provided that Matlab also have a JIT and supports Intel's MKL, it could beat this mark too. Any Matlab user would accept the challenge? -- Francesc Alted # The Computer Language Benchmarks Game # http://shootout.alioth.debian.org/ # # Contributed by Sebastien Loisel # Fixed by Isaac Gouy # Sped up by Josh Goldfoot # Dirtily sped up by Simon Descarpentries # Sped up with numpy by Kittipong Piyawanno # More speed-up with Numexpr by Francesc Alted from sys import argv import numpy as np import numexpr as ne def spectralnorm(n): u = np.matrix(np.ones(n)) j = np.arange(n, dtype=np.float64) M = np.empty(n*n, dtype=np.float64).reshape(n,n) expr = 1.0 / ((i + j) * (i + j + 1) / 2 + i + 1) for i in xrange(n): M[i] = ne.evaluate(expr) MT = M.T for i in xrange(10): v = (u*MT)*M u = (v*MT)*M print %0.9f % ((u*v.T).sum() / (v*v.T).sum())**0.5 spectralnorm(int(argv[1])) ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] debian benchmarks
Sturla Molden sturla at molden.no writes: It is also the kind of tasks where NumPy would help. It would be nice to get NumPy into the shootout. At least for the sake of advertising http://shootout.alioth.debian.org/u32/program.php?test=spectralnormlang=pythonid=2 ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] debian benchmarks
On Sun, Jul 4, 2010 at 4:32 AM, Sturla Molden stu...@molden.no wrote: I was just looking at Debian's benchmark. LuaJIT is now (on median) beating Intel Fortran! Consider that Lua is a dynamic language very similar to Python. I know it's just a benchmark but this has to count as insanely impressive. Beating Intel Fortran with a dynamic scripting language... How is that even possible? If this keeps up we'll need a Python to Lua compiler very soon. And LuaJIT 2 is rumoured to be much faster than the current... Looking at median runtimes, here is what I got: gcc 1.10 LuaJIT 1.96 Java 6 -server 2.13 Intel Fortran 2.18 OCaml 3.41 SBCL 3.66 JavaScript V8 7.57 PyPy 31.5 CPython 64.6 Perl 67.2 Ruby 1.9 71.1 This means that LuaJIT can do in less than a day what CPython can do in a month. The only comfort for CPython is that Ruby and Perl did even worse. I wonder how much better CPython would do with NumPy on this benchmark? Sturla Hi Sturla, what is this even about ... ? Do you have some references ? It does indeed sound interesting ... but what kind of code / problem are they actually testing here ? Thanks, Sebastian Haase ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] debian benchmarks
Sebastian Haase skrev: Hi Sturla, what is this even about ... ? Do you have some references ? It does indeed sound interesting ... but what kind of code / problem are they actually testing here ? http://shootout.alioth.debian.org/u32/which-programming-languages-are-fastest.php They are benchmarking with tasks that burns the CPU, like computing and bitmapping Mandelbrot sets and processing DNA data. Sturla ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] debian benchmarks
Sturla Molden skrev: http://shootout.alioth.debian.org/u32/which-programming-languages-are-fastest.php They are benchmarking with tasks that burns the CPU, like computing and bitmapping Mandelbrot sets and processing DNA data. It is also the kind of tasks where NumPy would help. It would be nice to get NumPy into the shootout. At least for the sake of advertising :-) ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
