# How to reduce RAM requirement in PETSC and SLEPCreading large binary matrices [closed]

I have two 50000 x 50000 binary matrices A and B for solving A*x=lambda*B*x eigenvalue problem. These matrices are sparse. I am trying to solve using PETSC and SLEPC. My memory requirement shoots off like more than 200 GB of RAM !

I used mpirun in 16 cores and 96GB RAM with swap of 130GB.

Is there a way to solve this problem.? Am I doing something wrong ? Kindly let me know.

## closed as off-topic by Bill Barth, Christian Clason, Brian Borchers, Godric Seer, GertVdEJan 28 '14 at 12:35

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• Please specify what algorithm you are using and -log_summary to show what the memory is being used for. How sparse are the matrices? – Jed Brown Jan 2 '14 at 13:18
• It certainly appears that you're storing your matrices in a dense format with lots of working matrices, rather than using a sparse format, since a dense 50,000 by 50,000 double precision matrix would require only 8*50,000*50,000=20 gigabytes of RAM. – Brian Borchers Jan 2 '14 at 19:55