Enhancing Memory Bandwidth in a Single Stream Computation with Multiple FPGAs

Antoniette Mondigo, K. Sano, H. Takizawa
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引用次数: 1

Abstract

Stream computing is an area where FPGAs can be suitably utilized to meet high performance and high scalability demands. To achieve these, a deep computing pipeline is implemented on multiple FPGAs where stream computing is performed. This paper presents an approach to utilize two masters in a 1D ring network of multiple FPGAs for a single stream computation. Each master FPGA will be reading and writing to their respective DDR3 memories alternately, while streaming through the slave FPGAs. This is done in order to synchronize the computational results on physically separate memory units. Due to this, the aggregate memory bandwidth is doubled, which suggests enhanced performance. The introduction of this streaming concept lays the groundwork towards full utilization of memories in all the FPGAs, as an identified future work.
用多个fpga增强单流计算中的内存带宽
流计算是fpga可以适当地用于满足高性能和高可扩展性需求的领域。为了实现这些,在多个fpga上实现了一个深度计算管道,其中执行流计算。本文提出了一种利用多个fpga组成的一维环形网络中的两个主网络进行单流计算的方法。每个主FPGA将交替地读取和写入各自的DDR3存储器,同时通过从FPGA进行流式传输。这样做是为了同步物理上独立的内存单元上的计算结果。因此,总内存带宽增加了一倍,这意味着性能得到了提高。这种流概念的引入为在所有fpga中充分利用存储器奠定了基础,作为确定的未来工作。
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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