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Performance optimization of Sparse Matrix-Vector Multiplication for multi-component PDE-based applications using GPUs.

, , , и . Concurr. Comput. Pract. Exp., 28 (12): 3447-3465 (2016)

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High Performance Multi-GPU SpMV for Multi-component PDE-Based Applications., , и . Euro-Par, том 9233 из Lecture Notes in Computer Science, стр. 601-612. Springer, (2015)Portable and Efficient Dense Linear Algebra in the Beginning of the Exascale Era., , , , , , , , и . P3HPC@SC, стр. 36-46. IEEE, (2022)Evaluating the Performance of NVIDIA's A100 Ampere GPU for Sparse and Batched Computations., , , , и . PMBS@SC, стр. 26-38. IEEE, (2020)Performance optimization of Sparse Matrix-Vector Multiplication for multi-component PDE-based applications using GPUs., , , и . Concurr. Comput. Pract. Exp., 28 (12): 3447-3465 (2016)Design, Optimization, and Benchmarking of Dense Linear Algebra Algorithms on AMD GPUs., , , и . HPEC, стр. 1-7. IEEE, (2020)Progressive Optimization of Batched LU Factorization on GPUs., , и . HPEC, стр. 1-6. IEEE, (2019)Factorization and Inversion of a Million Matrices using GPUs: Challenges and Countermeasures., , , и . ICCS, том 108 из Procedia Computer Science, стр. 606-615. Elsevier, (2017)Optimizing GPU Kernels for Irregular Batch Workloads: A Case Study for Cholesky Factorization., , , и . HPEC, стр. 1-7. IEEE, (2018)Towards Half-Precision Computation for Complex Matrices: A Case Study for Mixed Precision Solvers on GPUs., , и . ScalA@SC, стр. 17-24. IEEE, (2019)Performance, Design, and Autotuning of Batched GEMM for GPUs., , , и . ISC, том 9697 из Lecture Notes in Computer Science, стр. 21-38. Springer, (2016)