PHIST: a Pipelined, Hybrid-parallel Iterative Solver Toolkit
| Autor: | Dominik Ernst, Jonas Thies, Georg Hager, Nigel Overmars, Achim Basermann, Gerhard Wellein, Melven Röhrig-Zöllner |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Institut für Simulations- und Softwaretechnik
business.industry Computer science Applied Mathematics sparse matrices Context (language use) 010103 numerical & computational mathematics Parallel computing Solver Application software computer.software_genre 01 natural sciences 010101 applied mathematics Software Scalability High performance computing 0101 mathematics General-purpose computing on graphics processing units business Software architecture computer Block (data storage) eigenvalue computations sustainable software engineering |
| Popis: | The increasing complexity of hardware and software environments in high-performance computing poses big challenges on the development of sustainable and hardware-efficient numerical software. This article addresses these challenges in the context of sparse solvers. Existing solutions typically target sustainability, flexibility, or performance, but rarely all of them. Our new library PHIST provides implementations of solvers for sparse linear systems and eigenvalue problems. It is a productivity platform for performance-aware developers of algorithms and application software with abstractions that do not obscure the view on hardware-software interaction. The PHIST software architecture and the PHIST development process were designed to overcome shortcomings of existing packages. An interface layer for basic sparse linear algebra functionality that can be provided by multiple backends ensures sustainability, and PHIST supports common techniques for improving scalability and performance of algorithms such as blocking and kernel fusion. We showcase these concepts using the PHIST implementation of a block Jacobi-Davidson solver for non-Hermitian and generalized eigenproblems. We study its performance on a multi-core CPU, a GPU, and a large-scale many-core system. Furthermore, we show how an existing implementation of a block Krylov-Schur method in the Trilinos package Anasazi can benefit from the performance engineering techniques used in PHIST. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|