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Eigs in multinode cluster

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Wister Huang
Wister Huang on 18 May 2016
Edited: Andrew Knyazev on 12 Jun 2019
I am new to high performance computing and I am now trying to reconfigure one of my matlab code to a HPC.(I know it is probably not preferred, but I kind of need it in urgent.)
The task is to solve the lowest 6 eigen values for a 42500*42500 complex sparse Hermician matrix.
I have access to minimum 4 nodes and each node have more than 16GB memory.
I tried to submit this job but get an error
Out of memory. Type HELP MEMORY for your options.
Error in eigs/checkInputs/LUfactorAminusSigmaB (line 987)
[L,U,pp] = lu(AsB,'vector');
Error in eigs/checkInputs (line 809)
[L,U,pp,qq,dgAsB] = LUfactorAminusSigmaB;
Error in eigs (line 96)
Error in TwoDsolve (line 65)
Error in Loop_Main (line 9)
[psi,En] = TwoDsolve( V,m2Dx,m2Dy,Grd,'eigs',NOS);
Apparently it only use My question is: is there a way to configure eigs so that it can use all the memory I required from different nodes? I attach my submission file here as well.
#SBATCH --mail-type=ALL
#SBATCH --time=00:60:00
#SBATCH --nodes=4
#SBATCH --mem=16384
#SBATCH --ntasks=4
#SBATCH --cpus-per-task=4
echo "myjob.sub"
module load matlab/2016a
matlab -nodisplay -r Control
Thanks, Wister

Accepted Answer

Andrew Knyazev
Andrew Knyazev on 11 Aug 2018
Edited: Andrew Knyazev on 12 Jun 2019
EIGS has limited support for distributed memory, so you can run it only on a single node, but see the answer from Christine Tobler below.
Google, e.g., for LOBPCG implementations in BLOPEX, SLEPc, Trilinos, hypre, MAGMA for parallel MPI-based eigensolvers that scale to thousands of nodes and run on GPUs.
Revision 4.16 adds support for distributed or codistributed arrays available in MATLAB BigData toolbox, e.g.,:
A = codistributed(diag(1:100)); B = codistributed(diag(101:200));

More Answers (1)

Christine Tobler
Christine Tobler on 13 Aug 2018
The eigs function is supported for codistributed matrices in the Parallel Toolbox (see help codistributed/eigs. However, this version of eigs does not support the 'sm' / 'smallestabs' option (except for the case of a diagonal or triangular input matrix).
You could try to use the 'smallestreal' option instead, but this often has convergence issues, as it does not compute a decomposition of A, and also doesn't use a preconditioner, as LOBPCG typically does. However, this should be quick enough to try out, as it is just a one-liner.
  1 Comment
Christine Tobler
Christine Tobler on 13 Aug 2018
Sorry, I realize I started out with the details when I should have started more generally: To distribute a MATLAB array over several compute nodes, use the Parallel Toolbox, and its distributed or codistributed classes (< Parallel Toolbox Documentation>).

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