Optimization of Sparse Matrix Computation for Algebraic Multigrid on GPUs
AMG is one of the most efficient and widely used methods for solving sparse linear systems.
The computational process of AMG mainly consists of a series of iterative calculations of …
The computational process of AMG mainly consists of a series of iterative calculations of …
[HTML][HTML] Configurable sparse matrix-matrix multiplication accelerator on FPGA: A systematic design space exploration approach with quantization effects
High-performance sparse matrix multipliers are essential for deep learning applications, and
as big data analytics continues to evolve, specialized accelerators are also needed to …
as big data analytics continues to evolve, specialized accelerators are also needed to …
Optimizing sparse general matrix–matrix multiplication for DCUs
H Guo, H Wang, W Chen, C Zhang, Y Han… - The Journal of …, 2024 - Springer
Sparse general matrix–matrix multiplication (SpGEMM) is a crucial and complex
computational task in many practical applications. Improving the performance of SpGEMM …
computational task in many practical applications. Improving the performance of SpGEMM …
Generating Data Locality to Accelerate Sparse Matrix-Matrix Multiplication on CPUs
J Wolfson-Pou, J Laukemann, F Petrini - arXiv preprint arXiv:2501.07056, 2025 - arxiv.org
Sparse GEneral Matrix-matrix Multiplication (SpGEMM) is a critical operation in many
applications. Current multithreaded implementations are based on Gustavson's algorithm …
applications. Current multithreaded implementations are based on Gustavson's algorithm …
FLAASH: Flexible Accelerator Architecture for Sparse High-Order Tensor Contraction
G Kulp, A Ensinger, L Chen - arXiv preprint arXiv:2404.16317, 2024 - arxiv.org
Tensors play a vital role in machine learning (ML) and often exhibit properties best explored
while maintaining high-order. Efficiently performing ML computations requires taking …
while maintaining high-order. Efficiently performing ML computations requires taking …
Posudek oponenta závěrečné práce
M Šoch, BL Simulík - dspace.cvut.cz
Práce se zabývá paralelním násobením řídkých matic a obsahuje analýzu a porovnání
výkonu vlastního implementovaného algoritmu v OpenMP s existujícími algoritmy. Byly …
výkonu vlastního implementovaného algoritmu v OpenMP s existujícími algoritmy. Byly …