矩阵乘法在fpga上的面积和时间效率实现

Ju-wook Jang, S. Choi, V. Prasanna
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引用次数: 65

摘要

我们为可配置硬件上的矩阵乘法开发了新的算法和架构。这些设计大大减少了延迟和面积。我们的设计在面积/速度度量方面改进了以前的设计,其中速度表示最大可实现的运行频率。先前设计和我们设计的面积/速度指标分别为14.45,4.93和2.35,用于4 / sp1乘以/ 4矩阵乘法。之前的一种设计延迟为0.57 /spl mu/s,而我们的设计延迟为0.15 /spl mu/s,占地面积减少了18%。我们设计的面积比最著名的收缩设计小11% - 46%,具有相同延迟的大小为3 /spl倍/ 3 - 12 /spl倍/ 12的矩阵。性能改进往往随着问题的大小而增长。
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Area and time efficient implementations of matrix multiplication on FPGAs
We develop new algorithms and architectures for matrix multiplication on configurable hardware. These designs significantly reduce the latency as well as the area. Our designs improve the previous designs in terms of the area/speed metric where the speed denotes the maximum achievable running frequency. The area/speed metrics for the previous designs and our design are 14.45, 4.93, and 2.35, respectively, for 4 /spl times/ 4 matrix multiplication. The latency of one of the previous design is 0.57 /spl mu/s, while our design takes 0.15 /spl mu/s using 18% less area. The area of our designs is smaller by 11% - 46% compared with the best known systolic designs with the same latency for the matrices of sizes 3 /spl times/ 3 - 12 /spl times/ 12. The performance improvements tend to grow with the problem size.
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