FCUDA-SoC: Platform Integration for Field-Programmable SoC with the CUDA-to-FPGA Compiler

T. Nguyen, S. Gurumani, K. Rupnow, Deming Chen
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引用次数: 10

Abstract

Throughput oriented high level synthesis allows efficient design and optimization using parallel input languages. Parallel languages offer the benefit of parallelism extraction at multiple levels of granularity, offering effective design space exploration to select efficient single core implementations, and easy scaling of parallelism through multiple core instantiations. However, study of high level synthesis for parallel languages has concentrated on optimization of core and on-chip communications, while neglecting platform integration, which can have a significant impact on achieved performance. In this paper, we create an automated flow to perform efficient platform integration for an existing CUDA-to-RTL throughput oriented HLS, and we open source the FCUDA tool, platform integration, and benchmark applications. We demonstrate platform integration of 16 benchmarks on two Zynq-based systems in bare-metal and OS mode. We study implementation optimization for platform integration, compare to an embedded GPU (Tegra TK1) and verify designs on a Zedboard Zynq 7020 (bare-metal) and Omnitek Zynq 7045 (OS).
FCUDA-SoC:现场可编程SoC与cuda到fpga编译器的平台集成
面向吞吐量的高级合成允许使用并行输入语言进行有效的设计和优化。并行语言提供了在多个粒度级别上提取并行性的好处,提供了有效的设计空间探索,以选择高效的单核心实现,并通过多核心实例轻松扩展并行性。然而,并行语言的高级综合研究主要集中在核心和片上通信的优化上,而忽略了平台集成,这对实现的性能有重大影响。在本文中,我们创建了一个自动化流程,为现有的面向CUDA-to-RTL吞吐量的HLS执行有效的平台集成,并且我们开源了FCUDA工具、平台集成和基准测试应用程序。我们在裸机和操作系统模式下演示了两个基于zynq的系统上16个基准测试的平台集成。我们研究了平台集成的实现优化,与嵌入式GPU (Tegra TK1)进行了比较,并在Zedboard Zynq 7020(裸机)和Omnitek Zynq 7045 (OS)上验证了设计。
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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