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FPGA
2016
ACM

CASK: Open-Source Custom Architectures for Sparse Kernels

3 years 16 days ago
CASK: Open-Source Custom Architectures for Sparse Kernels
Sparse matrix vector multiplication (SpMV) is an important kernel in many scientific applications. To improve the performance and applicability of FPGA based SpMV, we propose an approach for exploiting properties of the input matrix to generate optimised custom architectures. The architectures generated by our approach are between 3.8 to 48 times faster than the worst case architectures for each matrix, showing the benefits of instance specific design for SpMV.
Paul Grigoras, Pavel Burovskiy, Wayne Luk
Added 03 Apr 2016
Updated 03 Apr 2016
Type Journal
Year 2016
Where FPGA
Authors Paul Grigoras, Pavel Burovskiy, Wayne Luk
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