A matrix multiplier case study for an evaluation of a configurable dataflow-machine

L. Verdoscia, R. Vaccaro, R. Giorgi
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引用次数: 14

Abstract

Configurable computing has become a subject of a great deal of research given its potential to greatly accelerate a wide variety of applications that require high throughput. In this context, the dataflow approach is still promising to accelerate the kernel of applications in the field of HPC. That tanks to a computational dataflow engine able to execute dataflow program graphs directly in a custom hardware. On the other hand, evaluating radically different models of computation remains yet an open issue. In this paper we present as case study the matrix multiplication that constitutes the fundamental kernel of the linear algebra. The evaluation takes into account the execution of the matrix product both in non-pipelined and pipelined modes. Results obtained running the execution of the two modes on an FPGA-based demonstrator show the validity of the configurable Dataflow-Machine. Moreover, at the same throughput, the power consumption is expected to be lower than in clock-based systems.
一个矩阵乘法器案例研究,用于可配置数据流机器的评估
由于可配置计算具有极大地加快各种需要高吞吐量的应用程序的潜力,因此它已成为大量研究的主题。在这种背景下,数据流方法仍有望加速高性能计算领域的核心应用。这就需要一个能够在定制硬件中直接执行数据流程序图的计算数据流引擎。另一方面,评估完全不同的计算模型仍然是一个悬而未决的问题。在本文中,我们提出了作为案例研究矩阵乘法,它构成了线性代数的基本核心。评估考虑了矩阵乘积在非流水线和流水线模式下的执行。在基于fpga的验证机上运行两种模式的结果表明了可配置数据流机的有效性。此外,在相同的吞吐量下,功耗预计将低于基于时钟的系统。
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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