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Exploiting memory customization in FPGA for 3D stencil computations

机译:利用FPGA中的内存定制功能进行3D模板计算

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3D stencil computations are compute-intensive kernels often appearing in high-performance scientific and engineering applications. The key to efficiency in these memory-bound kernels is full exploitation of data reuse. This paper explores the design aspects for 3D-Stencil implementations that maximize the reuse of all input data on a FPGA architecture. The work focuses on the architectural design of 3D stencils with the form n × (n + 1) × n, where n = {2, 4, 6, 8, …}. The performance of the architecture is evaluated using two design approaches, “Multi-Volume” and “Single-Volume”. When n = 8, the designs achieve a sustained throughput of 55.5 GFLOPS in the “Single-Volume” approach and 103 GFLOPS in the “Multi-Volume” design approach in a 100–200MHz multi-rate implementation on a Virtex-4 LX200 FPGA. This corresponds to a stencil data delivery of 1500 bytes/cycle and 2800 bytes/cycle respectively. The implementation is analyzed and compared to two CPU cache approaches and to the statically scheduled local stores on the IBM PowerXCell 8i. The FPGA approaches designed here achieve much higher bandwidth despite the FPGA device being the least recent of the chips considered. These numbers show how a custom memory organization can provide large data throughput when implementing 3D stencil kernels.
机译:3D模板计算是计算密集型内核,通常出现在高性能科学和工程应用程序中。这些内存绑定内核中提高效率的关键是充分利用数据重用。本文探讨了3D-Stencil实现的设计方面,这些实现可最大程度地重用FPGA架构上所有输入数据。这项工作集中在形式为n×(n + 1)×n的3D模板的建筑设计上,其中n = {2,4,6,6,…}。使用“多卷”和“单卷”两种设计方法评估体系结构的性能。当n = 8时,在Virtex-4 LX200 FPGA上以100–200MHz多速率实现,设计在“单卷”方法中实现了55.5 GFLOPS的持续吞吐量,在“多卷”设计方法中实现了103 GFLOPS的持续吞吐量。 。这分别对应于1500字节/周期和2800字节/周期的模板数据传递。对该实现进行了分析,并与两种CPU缓存方法以及IBM PowerXCell 8i上的静态调度本地存储进行了比较。尽管FPGA器件是考虑中的最新芯片,但此处设计的FPGA方法可实现更高的带宽。这些数字显示了自定义内存组织如何在实施3D模具内核时提供大数据吞吐量。

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