SPARTA: High-Level Synthesis of Parallel Multi-Threaded Accelerators

Giovanni Gozzi, M. Fiorito, S. Curzel, Claudio Barone, Vito Giovanni Castellana, Marco Minutoli, Antonino Tumeo, Fabrizio Ferrandi
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Abstract

This paper presents a methodology for the Synthesis of PARallel multi-Threaded Accelerators (SPARTA) from OpenMP annotated C/C++ specifications. SPARTA extends an open-source HLS tool, enabling the generation of accelerators that provide latency tolerance for irregular memory accesses through multithreading, support fine-grained memory-level parallelism through a hot-potato deflection-based network-on-chip (NoC), support synchronization constructs, and can instantiate memory-side caches. Our approach is based on a custom runtime OpenMP library, providing flexibility and extensibility. Experimental results show high scalability when synthesizing irregular graph kernels. The accelerators generated with our approach are, on average, 2.29x faster than state-of-the-art HLS methodologies.
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SPARTA:并行多线程加速器的高层合成
本文介绍了一种根据 OpenMP 注释的 C/C++ 规范合成 PARallel 多线程加速器(SPARTA)的方法。SPARTA 扩展了开源 HLS 工具,使生成的加速器能够通过多线程为不规则内存访问提供延迟容差,通过基于热土豆偏转的片上网络(NoC)支持细粒度内存级并行,支持同步构造,并能实例化内存侧缓存。我们的方法基于定制的运行时 OpenMP 库,具有灵活性和可扩展性。实验结果表明,在合成不规则图内核时具有很高的可扩展性。使用我们的方法生成的加速器平均比最先进的 HLS 方法快 2.29 倍。
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