modelBSE

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laurent_pedesseau1
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modelBSE

#1 Post by laurent_pedesseau1 » Tue Aug 31, 2021 2:49 pm

Dear VASP Admin, VASP colleagues,

We are working with the very nice modelBSE method. I found a technical bottleneck for the parallelization this method use only NPAR=total number of cores.

This is not practical if you are increasing the number of k-point which hugely increases the memory per core. In principle, one can play with kpar or ncore and npar to decrease the memory per node.

So my question: Have you a way of decreasing the memory per node? instead of using kpar, ncore, etc.

Sincerely,

Laurent Pedesseau

ferenc_karsai
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Re: modelBSE

#2 Post by ferenc_karsai » Mon Sep 06, 2021 8:54 am

The large arrays for BSE (also modelBSE) are distributed by scaLAPACK. So increasing the number of cores in the calculation should bring down the amount of memory needed per core.

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Re: modelBSE

#3 Post by laurent_pedesseau1 » Mon Sep 06, 2021 9:15 am

In the limit of having NPAR=total number of cores and NBAND/NPAR... However when we use the modelBSE, in principle, we need a huge amount of k-point which is increasing a lot the memory more than NBAND.

Many thanks for your reply

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Re: modelBSE

#4 Post by ferenc_karsai » Mon Sep 06, 2021 9:20 am

The block-cyclic distribution via scaLAPACK is apparent for NPAR/NCORE values. The important line is "BSE (scaLAPACK) attempting allocation of XXX Gbyte". This scales almost linearly with increasing number of cores.

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