A universal FPGA-based floating-point matrix processor for mobile systems

Wenqiang Wang, Kaiyuan Guo, Mengyuan Gu, Yuchun Ma, Yu Wang
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引用次数: 6

Abstract

FPGA-based acceleration of matrix operations is a promising solution in mobile systems. However, most related work focuses on a certain operation instead of a complete system. In this paper, we explore the possibility of integrating multiple matrix accelerators with a master processor and propose a universal floating-point matrix processor. The processor supports multiple matrix-matrix operations (Level 3 BLAS) and the matrix size is unlimited. The key component of the processor is a shared matrix cache which enables on-chip communication between different accelerators. This structure reduces the external memory bandwidth requirement and improves the overall performance. Considering the performance of the whole system, an asynchronous instruction execution mechanism is further proposed in the hardware-software interface so as to reduce the workload of the master processor. We demonstrate the system using a DE3 develop board and achieve a computing performance of about 19 GFLOPS. Experiments show the proposed processor achieves higher performance and energy efficiency than some state-of-the-art embedded processors including ARM cortex A9 and NIOS Il/f soft-core processor. The performance of the processor is even comparable to some desktop processors.
一种通用的基于fpga的移动系统浮点矩阵处理器
基于fpga的矩阵运算加速是移动系统中一个很有前途的解决方案。然而,大多数相关工作都集中在某个操作上,而不是一个完整的系统。本文探讨了用一个主处理器集成多个矩阵加速器的可能性,并提出了一个通用浮点矩阵处理器。该处理器支持多重矩阵-矩阵运算(Level 3 BLAS),矩阵大小不限。处理器的关键组件是一个共享矩阵缓存,它使不同加速器之间的片上通信成为可能。这种结构降低了外部内存带宽需求,提高了整体性能。考虑到整个系统的性能,在硬件软件接口上进一步提出了异步指令执行机制,以减少主处理器的工作量。我们使用DE3开发板对系统进行了演示,并实现了约19 GFLOPS的计算性能。实验表明,该处理器比ARM cortex A9和NIOS Il/f软核处理器具有更高的性能和能效。处理器的性能甚至可以与一些桌面处理器相媲美。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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