[petsc-users] Benchmarking

[Jose E. Roman]

> El 28 dic 2016, a las 16:26, Vijay Gopal Chilkuri <vijay.gopal.c at gmail.com> escribió:
> 
> Dear developers,
> 
> I'm doing exact diagonalization studies of some phenomenological model Hamiltonian. In this study I have to diagonalize large sparse matrices in Hilbert space of Slater determinants many times.
> 
> I've successfully used PETSc + SLEPc to get few smallest eigenvalues. 
> For example I've been able to diagonalize a matrix of rank 91454220 with 990 processors. This diagonalization took 15328.695847 Sec (or 4.25 Hrs.)
> 
> I have two questions:
> 
> 1. Is this time reasonable, if not, is it possible to optimize further ?

It depends on how many eigenvalues are being computed. If computing more than 1000 eigenvalues it is very important to set the mpd parameter, see section 2.6.5.

> 
> 2. I've tried a quick google search but could not find a comprehensive benchmarking of the SLEPc library for sparse matrix diagonalization. Could you point me to a publication/resource which has such a benchmarking ?

Some papers in the list of applications have performance results.
http://slepc.upv.es/material/appli.htm
See for instance [Moran et al 2011] for results up to 2048 cores. See also [Steiger et al 2011].

Jose


> 
> Thanks for your help.
> 
> PETSc Version: master branch commit: b33322e
> SLEPc Version: master branch commit: c596d1c 
> 
> Best,
>  Vijay
> 
>