Fast Matlab compatible sparse assembly on multicore computers

TL;DR

This paper presents a highly efficient, parallel sparse matrix assembly algorithm compatible with Matlab, significantly accelerating the process on multicore systems by a factor of up to 10.

Contribution

The paper introduces a novel parallel sparse assembly algorithm that is fully Matlab compatible and demonstrates substantial speed improvements over existing implementations.

Findings

Achieves 5x speedup on 6-core machines

Achieves 10x speedup on 16-core machines

Provides freely available Matlab-compatible code

Abstract

We develop and implement in this paper a fast sparse assembly algorithm, the fundamental operation which creates a compressed matrix from raw index data. Since it is often a quite demanding and sometimes critical operation, it is of interest to design a highly efficient implementation. We show how to do this, and moreover, we show how our implementation can be parallelized to utilize the power of modern multicore computers. Our freely available code, fully Matlab compatible, achieves about a factor of 5 times in speedup on a typical 6-core machine and 10 times on a dual-socket 16 core machine compared to the built-in serial implementation.