Re: [eigen] slides of my talk |

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*To*: eigen@xxxxxxxxxxxxxxxxxxx*Subject*: Re: [eigen] slides of my talk*From*: Andre Krause <post@xxxxxxxxxxxxxxxx>*Date*: Mon, 26 Jan 2009 16:46:59 +0100*Organization*: http://www.coreloop.com

Gael Guennebaud schrieb: well, it seems as if there was something done by the matlab team since version 6.5 of matlab. see this link: http://www.caspur.it/risorse/softappl/doc/matlab_help/techdoc/matlab_prog/ch7_pe11.html Operating System MATLAB 6.1 MATLAB 6.5 Performance Gain Windows 1 min., 25.9 sec. 1.1 sec. x 78.1 Linux 3 min., 13.8 sec. 1.7 sec. x 114.0 Solaris 8 min., 51.0 sec. 23.5 sec. x 22.6 looking at those results, it would be even more interesting, how well matlab does now compared to native c++. seems as if they indeed added some jit compiler... p.s. just googled - and found this: http://www.mathworks.se/products/matlab/whatsnew.html so matlab really has JIT acceleration. > indeed, if you use matlab on relatively large dataset and you only use > high level operators/routines then matlab is very fast because it > relies on other state of the art library. There even exists plugins to > perform some computations on the GPU... > > Said that, matlab is extremely slow as soon as you are doing some more > low level stuff involving complex expressions or a lot of small > computations... Matlab can be a couple of order of magnitude slower > than a C/C++ equivalent code. It seems MatLab is missing a JIT > compiler. > > btw, benoit thanks for the slides ! > > Gael. > > On Mon, Jan 26, 2009 at 3:35 PM, Benoit Jacob <jacob.benoit.1@xxxxxxxxx> wrote: >> I have no clue how matlab does in general, but on the forum we've had >> a user benchmarking matrix product against matlab, and matlab was >> doing like MKL and Goto, which suggests that it's using one of these >> libraries. >> >> If you're on *nix, you could try ldd or nm to get a clue about what >> library they're using. >> >> Cheers, >> Benoit >> >> 2009/1/26 Andre Krause <post@xxxxxxxxxxxxxxxx>: >>> Benoit Jacob schrieb: >>>> Hi, >>>> >>>> Today morning I gave a talk on Eigen at the CS department. Here are my >>>> slides, in case they might be helpful. >>>> When you see (SHOW BENCHMARKS) that's where I showed the benchmark >>>> graphs that are displayed on the Benchmark page of the wiki. >>>> I didn't have time to cover the last part on Eigen internals, I just >>>> finished with the benchmarks. However people were interested and asked >>>> questions about internals so in effect I got to explain as much of the >>>> internals as I had planned to. >>>> >>>> Thanks a LOT to Keir: he translated the C++ snippets into Matlab for >>>> me, and gave me a good briefing as to how to organize a talk for an >>>> audience of CS people. >>>> >>>> I am just afraid that using \documentclass{slides} for a public of CS >>>> people makes me look like a dinosaur mathematician. >>>> >>>> Cheers, >>>> Benoit >>> dear benoit, you show matlab code corresponding to eigen2 code. but in the >>> benchmark section on the wiki, there is no matlab benchmark. i would be very >>> curious how slow (or fast?) matlab is, compared to eigen. i teached myself >>> matlab over christmas, and now i am curious how matlab compares to c++ (with >>> eigen2). >>> >>> >>> >> >> > > >

**Follow-Ups**:**Re: [eigen] slides of my talk***From:*Benoit Jacob

**References**:**[eigen] slides of my talk***From:*Benoit Jacob

**Re: [eigen] slides of my talk***From:*Andre Krause

**Re: [eigen] slides of my talk***From:*Benoit Jacob

**Re: [eigen] slides of my talk***From:*Gael Guennebaud

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