Optimizing Sparse Matrix—Matrix Multiplication for the GPU

DOI10.1145/2699470zbMath1347.65085OpenAlexW1980282429WikidataQ113310260 ScholiaQ113310260MaRDI QIDQ2828151

Steven Dalton, Luke N. Olson, Nathan Bell

Publication date: 24 October 2016

Published in: ACM Transactions on Mathematical Software (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1145/2699470

zbMATH Keywords

sparse matricesparallel algorithmsGPUmatrix-matrix multiplication

Mathematics Subject Classification ID

Related Items (6)

Memory-Efficient Sparse Matrix-Matrix Multiplication by Row Merging on Many-Core Architectures ⋮ GraphBLAST: A High-Performance Linear Algebra-based Graph Framework on the GPU ⋮ A two-scale approach for efficient on-the-fly operator assembly in massively parallel high performance multigrid codes ⋮ A New Class of AMG Interpolation Methods Based on Matrix-Matrix Multiplications ⋮ Reducing Communication Costs for Sparse Matrix Multiplication within Algebraic Multigrid ⋮ Exploiting Multiple Levels of Parallelism in Sparse Matrix-Matrix Multiplication

Uses Software

• CUDA
• PETSc
• Trilinos
• SparseMatrix
• CUSP
• Thrust
• SMMP

Cites Work

• Unnamed Item
• Sparse matrix multiplication package (SMMP)
• The university of Florida sparse matrix collection
• Maximum matchings in general graphs through randomization
• Exposing Fine-Grained Parallelism in Algebraic Multigrid Methods
• Parallel Sparse Matrix-Matrix Multiplication and Indexing: Implementation and Experiments
• An overview of the Trilinos project
• Using Mixed Precision for Sparse Matrix Computations to Enhance the Performance while Achieving 64-bit Accuracy
• Two Fast Algorithms for Sparse Matrices: Multiplication and Permuted Transposition

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