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Nov 6, 2014 · In this paper, we propose two novel methods to optimize the memory bandwidth for SpMV on GPGPU. First, a new storage format is proposed to ...
Memory bandwidth optimization of SpMV on GPGPUs. 433. Therefore, COO method offers robust performance across a wide variety of sparse matrices. One drawback ...
In this paper, we propose two novel methods to optimize the memory bandwidth for SpMV on GPGPU. First, a new storage format is proposed to exploit memory ...
Bibliographic details on Memory bandwidth optimization of SpMV on GPGPUs.
Abstract—In this paper, we investigate the relative merits between GPGPUs and multicores in the context of sparse matrix-vector multiplication (SpMV).
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Apr 13, 2022 · The global memory is connected to the GPU chip wich. DDR/HBM memory interface with limited bandwidth (which is 900 GB/s for Tesla V100 used ...
Therefore, we need to parallelize and optimize SpMV on GPGPU to get a better performance. ... There are many existing SpMV optimization ... Kennedy, “The memory ...
Memory bandwidth optimization of SpMV on GPGPUs. It is an important task to improve performance for sparse matrix vector multiplication (SpMV), and it is a ...
The most important factors affecting the SpMV performance are the memory bandwidth limitation and the high cache-miss rate caused by the irregular and indirect ...
Apr 8, 2023 · Memory bandwidth optimization of SpMV on GPGPUs. It is an important task to improve performance for sparse matrix vector multiplication (SpMV) ...