Bin-VBSR: Variable Block Size Binned Block-Compressed Sparse Row for Efficient GPU-Accelerated Finite Element Analysis
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Date
2025
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
We present Binned Variable Block Compressed Sparse Row (Bin-VBSR), a novel GPU-optimized sparse matrix data structure and associated sparse matrix-vector multiplication algorithm for matrices with variable-size dense blocks. This includes a novel approach to handling long rows in the Binned Compressed Sparse Row (Bin-CSR) family of GPU-optimized sparse matrix data structures. We demonstrate speedups of up to 9.9× over Bin-BCSR* and extend its data compression advantages over compressed sparse row (CSR) to variable block size, resulting in an improvement of up to 50%.
Description
CCS Concepts: Computing methodologies → Massively parallel algorithms; Mathematics of computing → Computations on matrices; Mathematical software performance
@inproceedings{10.2312:vmv.20251245,
booktitle = {Vision, Modeling, and Visualization},
editor = {Egger, Bernhard and Günther, Tobias},
title = {{Bin-VBSR: Variable Block Size Binned Block-Compressed Sparse Row for Efficient GPU-Accelerated Finite Element Analysis}},
author = {Pfeil, Florian and Ferreira, Stephanie and Mueller-Roemer, Johannes Sebastian},
year = {2025},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-294-3},
DOI = {10.2312/vmv.20251245}
}