Affiliation:
1. Lawrence Berkeley National Laboratory, Berkeley, CA
2. Oak Ridge National Laboratory, Oak Ridge, TN
Abstract
We present the new features available in the recent release of
SuperLU_DIST
, Version 8.1.1.
SuperLU_DIST
is a distributed-memory parallel sparse direct solver. The new features include (1) a 3D communication-avoiding algorithm framework that trades off inter-process communication for selective memory duplication, (2) multi-GPU support for both NVIDIA GPUs and AMD GPUs, and (3) mixed-precision routines that perform single-precision LU factorization and double-precision iterative refinement. Apart from the algorithm improvements, we also modernized the software build system to use CMake and Spack package installation tools to simplify the installation procedure. Throughout the article, we describe in detail the pertinent performance-sensitive parameters associated with each new algorithmic feature, show how they are exposed to the users, and give general guidance of how to set these parameters. We illustrate that the solver’s performance both in time and memory can be greatly improved after systematic tuning of the parameters, depending on the input sparse matrix and underlying hardware.
Funder
Exascale Computing Project
U.S. Department of Energy Office of Science
National Nuclear Security Administration
Publisher
Association for Computing Machinery (ACM)
Subject
Applied Mathematics,Software
Cited by
2 articles.
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