Matlab p 2 0 user friendly interactive environment for parallel scientific computing
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MATLAB*P 2.0: User Friendly, Interactive Environment for Parallel Scientific Computing. Ron Choy, Alan Edelman Lab. For Computer Science MIT. MATLAB*P: a parallel MATLAB project. We all love MATLAB It’s useful for numerical experiments as well as for real production systems

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MATLAB*P 2.0: User Friendly, Interactive Environment for Parallel Scientific Computing

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Matlab p 2 0 user friendly interactive environment for parallel scientific computing

MATLAB*P 2.0: User Friendly, Interactive Environment for Parallel Scientific Computing

Ron Choy, Alan Edelman

Lab. For Computer Science

MIT


Matlab p a parallel matlab project

MATLAB*P: a parallel MATLAB project

  • We all love MATLAB

  • It’s useful for numerical experiments as well as for real production systems

  • Don’t you wish it runs faster?


Outline

Outline

  • Project background

  • The system

  • How to use?

  • Benchmarks


Why parallel matlab

Why parallel MATLAB

  • MATLAB only runs on single processor

  • It was fine before, but the size of interesting problems grows faster than CPU speed

  • Solution:

    • Use compiled language – hard(er)

    • Make a parallel MATLAB


Parallel matlab survey

Parallel MATLAB Survey

  • 26 projects

  • 4 approaches

    • Message passing

    • Embarrassingly parallel

    • Compilation

    • Backend support MATLAB*P


Matlab p

MATLAB*P

  • Provide a parallel backend to MATLAB

  • Backend is based on popular numerical libraries:

    • ScaLAPACK

    • FFTW

    • PARPACK


Focus

Focus

  • Require minimal learning on user’s part

  • Reuse of existing scripts

  • Mimic MATLAB behaviour

  • Data stay on backend until explicitly retrieved by user

  • Extendable backend


Example

Example

  • A = randn(1024*p,1024*p);

  • E = eig(A);

  • e = pp2matlab(E);

  • plot(e,’*’);


Example 2

Example 2

  • J = 1:n;

  • J = J(ones(n,1),:);

  • I = J’;

  • E = ones(n,n);

  • H = E./(I+J-1);


Example 3

Example 3

  • d = randn(10000*p,1);

  • a = 1:9999*P;

  • z = mm(‘chi2rnd’,a);

  • e = stebz(d,z)


Example 4

Example 4

  • Index = 1:100*p;

  • B = mm(‘mywork’, Index);


Visualization package

Visualization package

  • A term project done by a group of students in a parallel computing class at MIT

  • Provides the equivalent of mesh, surf and spy to distributed matrices


Benchmarks

Benchmarks

  • Does all this power and convenience come at a cost?

  • Sadly it does

    • Communication between MATLAB and server

    • Data distribution to mimic MATLAB

  • Good news: it amortizes


To obtain more information

To obtain more information …

  • Parallel MATLAB survey

    • http://supertech.lcs.mit.edu/~cly/survey.html

  • MATLAB*P homepage

    • http://supertech.lcs.mit.edu/~cly/matlabp.html

  • My email address: [email protected]


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