distributed memory version about strumpack HOT 1 OPEN

Hi Mike,
The sparse direct solver does support distributed memory, relying on MPI and ScaLAPACK.
Sierra is a GPU machine, much like summit, correct? We also have GPU support.
For a single GPU, we use CUDA and cuBLAS/cuSOLVER. To run on multiple nodes, with multiple GPUs, we use SLATE (https://bitbucket.org/icl/slatehttps://bitbucket.org/icl/slate) as well as CUDA.
Here is more info on the installation process:
https://portal.nersc.gov/project/sparse/strumpack/master/installation.html

Apart from the sparse direct solver, we also have distributed memory preconditioners, based on approximate factorization.
This uses rank-structured matrix approximations, like Hierarchically Semi-Separable, Hierarchically Off-Diagonal Low-Rank, Block Low Rank and Butterfly matrix decompositions. These preconditioners are also aimed at large sparse problems from for instance FEM codes. See for instance here:
https://portal.nersc.gov/project/sparse/strumpack/master/HSS_Preconditioning.html

We'd be happy to work with you.

from strumpack.