OpenCL-ready High Speed FPGA Network for Reconfigurable High Performance Computing

Ryohei Kobayashi, Yuma Oobata, N. Fujita, Y. Yamaguchi, T. Boku
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引用次数: 41

Abstract

Field programmable gate arrays (FPGAs) have gained attention in high-performance computing (HPC) research because their computation and communication capabilities have dramatically improved in recent years as a result of improvements to semiconductor integration technologies that depend on Moore's Law. In addition to FPGA performance improvements, OpenCL-based FPGA development toolchains have been developed and offered by FPGA vendors, which reduces the programming effort required as compared to the past. These improvements reveal the possibilities of realizing a concept to enable on-the-fly offloading computation at which CPUs/GPUs perform poorly to FPGAs while performing low-latency data movement. We think that this concept is one of the keys to more improve the performance of modern heterogeneous supercomputers using accelerators like GPUs. In this paper, we propose high-performance inter-FPGA Ethernet communication using OpenCL and Verilog HDL mixed programming in order to demonstrate the feasibility of realizing this concept. OpenCL is used to program application algorithms and data movement control when Verilog HDL is used to implement low-level components for Ethernet communication. Experimental results using ping-pong programs showed that our proposed approach achieves a latency of 0.99 μs and as much as 4.97 GB/s between FPGAs over different nodes, thus confirming that the proposed method is effective at realizing this concept.
面向可重构高性能计算的OpenCL-ready高速FPGA网络
现场可编程门阵列(fpga)在高性能计算(HPC)研究中受到关注,因为近年来依赖摩尔定律的半导体集成技术的改进使其计算和通信能力得到了显着提高。除了FPGA性能改进之外,FPGA供应商还开发并提供了基于opencl的FPGA开发工具链,与过去相比,这减少了所需的编程工作量。这些改进揭示了实现一个概念的可能性,即cpu / gpu在执行低延迟数据移动时对fpga表现不佳,从而实现动态卸载计算。我们认为这个概念是使用gpu等加速器进一步提高现代异构超级计算机性能的关键之一。本文提出了基于OpenCL和Verilog HDL混合编程的高性能fpga间以太网通信,以证明实现该概念的可行性。使用OpenCL编程应用算法和数据移动控制,使用Verilog HDL实现以太网通信的底层组件。利用乒乓程序进行的实验结果表明,我们提出的方法在不同节点上fpga之间的延迟为0.99 μs,延迟高达4.97 GB/s,从而证实了我们提出的方法在实现这个概念方面是有效的。
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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