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Open access Oct 2026

Demystifying SpMV Performance: Bottleneck Characterization and Open Challenges

Sparse Matrix-Vector Multiplication (SpMV) is a critical computational kernel in scientific computing, graph processing, and machine learning. Despite its importance, SpMV achieves only a small fraction of peak performance, varying substantially across matrices and architectures. This paper comprehensively analyzes SpM...

Panagiotis Mpakos, Dimitrios Galanopoulos, Petros Anastasiadis et al. · 0 citations

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