Performance Optimization Using Partitioned SpMV on GPUs and Multicore CPUs

DOI10.1109/TC.2014.2366731zbMath1360.65135OpenAlexW2025890876MaRDI QIDQ2982112

KenLi Li, Keqin Li, Wangdong Yang, Ze-Yao Mo

Publication date: 16 May 2017

Published in: IEEE Transactions on Computers (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1109/tc.2014.2366731

Mathematics Subject Classification ID

Computational methods for sparse matrices (65F50) Symbolic computation and algebraic computation (68W30) Parallel numerical computation (65Y05) Numerical algorithms for specific classes of architectures (65Y10) Software, source code, etc. for problems pertaining to numerical analysis (65-04)

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A noise-suppressing Newton-Raphson iteration algorithm for solving the time-varying Lyapunov equation and robotic tracking problems ⋮ Portable implementation model for CFD simulations. Application to hybrid CPU/GPU supercomputers ⋮ tpSpMV: a two-phase large-scale sparse matrix-vector multiplication kernel for manycore architectures ⋮ A parallel computing method using blocked format with optimal partitioning for SpMV on GPU ⋮ Advantages of static condensation in implicit compressible Navier-Stokes DGSEM solvers ⋮ EGC: entropy-based gradient compression for distributed deep learning

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