Re: [eigen] slides of my talk

[Andre Krause <post@xxxxxxxxxxxxxxxx>]

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).
>>>
>>>
>>>
>>
>>
> 
> 
>