English

Verification Challenges in Sparse Matrix Vector Multiplication in High Performance Computing: Part I

Logic in Computer Science 2025-10-16 v1 Distributed, Parallel, and Cluster Computing Mathematical Software

Abstract

Sparse matrix vector multiplication (SpMV) is a fundamental kernel in scientific codes that rely on iterative solvers. In this first part of our work, we present both a sequential and a basic MPI parallel implementations of SpMV, aiming to provide a challenge problem for the scientific software verification community. The implementations are described in the context of the PETSc library.

Keywords

Cite

@article{arxiv.2510.13427,
  title  = {Verification Challenges in Sparse Matrix Vector Multiplication in High Performance Computing: Part I},
  author = {Junchao Zhang},
  journal= {arXiv preprint arXiv:2510.13427},
  year   = {2025}
}

Comments

In Proceedings VSS 2025, arXiv:2510.12314

R2 v1 2026-07-01T06:38:43.164Z