Efficient FPGA-based sparse matrix-vector multiplication with data reuse-aware compression

• المؤلفون الرئيسيون: Li, Shiqing, Liu, Di, Liu, Weichen
• مؤلفون آخرون: School of Computer Science and Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2023
• الموضوعات: Engineering::Computer science and engineering; Engineering::Computer science and engineering::Hardware; SpMV; FPGA; Data Reuse; Throughput
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/169152
• المؤسسة: Nanyang Technological University

Sparse matrix-vector multiplication (SpMV) on FPGAs has gained much attention. The performance of SpMV is mainly determined by the number of multiplications between non-zero matrix elements and the corresponding vector values per cycle. On the one side, the off-chip memory bandwidth limits the numbe...