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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. 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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  1. MATLAB*P 2.0: User Friendly, Interactive Environment for Parallel Scientific Computing Ron Choy, Alan Edelman Lab. For Computer Science MIT

  2. 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?

  3. Outline • Project background • The system • How to use? • Benchmarks

  4. 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

  5. Parallel MATLAB Survey • 26 projects • 4 approaches • Message passing • Embarrassingly parallel • Compilation • Backend support MATLAB*P

  6. MATLAB*P • Provide a parallel backend to MATLAB • Backend is based on popular numerical libraries: • ScaLAPACK • FFTW • PARPACK • …

  7. 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

  8. Example • A = randn(1024*p,1024*p); • E = eig(A); • e = pp2matlab(E); • plot(e,’*’);

  9. Example 2 • J = 1:n; • J = J(ones(n,1),:); • I = J’; • E = ones(n,n); • H = E./(I+J-1);

  10. Example 3 • d = randn(10000*p,1); • a = 1:9999*P; • z = mm(‘chi2rnd’,a); • e = stebz(d,z)

  11. Example 4 • Index = 1:100*p; • B = mm(‘mywork’, Index);

  12. 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

  13. 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

  14. 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: cly@mit.edu

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