Accelerating Space Radiative Transfer on FPGA using OpenCL
Accelerating Space Radiative Transfer on FPGA using OpenCL
复制标题
使用 OpenCL 加速 FPGA 上的空间辐射传输
DOI：
10.1145/3241793.3241799
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
M. Umemura
中科院分区：
文献类型：
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作者：
N. Fujita;Ryohei Kobayashi;Y. Yamaguchi;Yuma Oobata;T. Boku;Makito Abe;K. Yoshikawa;M. Umemura
高性能计算（HPC）所面临的最新挑战之一是如何应用现场可编程门阵列（FPGA）技术来加速下一代超级计算机，作为实现高性能和低功耗的有效方法。图形处理单元（GPU）是HPC最常用的加速器，它需要定期执行高度并行的操作，这在某些情况下会导致性能瓶颈。另一方面，在逻辑电路中灵活有效地利用FPGA来适应各种计算情况有很大的机会。然而，对于应用开发者来说，要为他们的应用和算法实现FPGA逻辑电路并不容易，这通常需要复杂的硬件逻辑描述。由于近年来FPGA开发环境的进步，使用OpenCL语言的高级综合（HLS）开发环境已经变得流行。根据我们使用OpenCL描述内核的经验，我们发现，一个更积极的编程策略是必要的，以实现真正的高性能的基础上的“协同设计”的概念，实现必要的功能和操作，以适应目标应用程序的FPGA设计。在本文中，我们优化的真实辐射传输（ART）的方法在FPGA上使用OpenCL。我们还讨论了在FPGA中并行计算的方法和在FPGA上优化OpenCL代码的方法。使用一种协同设计的方法来优化FPGA中OpenCL的特定应用程序的编程，我们实现了比使用OpenMP的CPU实现快6.9倍的性能，并且与使用CUDA的GPU实现几乎相同的性能。ART代码应该在具有多个FPGA的较大配置上工作，这些FPGA之间需要互连。考虑到目前先进的FPGA的互连功能，我们相信，他们的并行实现与多个FPGA将实现更高的性能比GPU。
One of the recent challenges faced by High-Performance Computing (HPC) is how to apply Field-Programmable Gate Array (FPGA) technology to accelerate a next-generation supercomputer as an efficient method of achieving high performance and low power consumption. Graphics Processing Unit (GPU) is the most commonly used accelerator for HPC supported by regularly executed high degree of parallel operations which causes performance bottleneck in some cases. On the other hand, there are great opportunities to flexibly and efficiently utilize FPGAs in logic circuits to fit various computing situations. However, it is not easy for application developers to implement FPGA logic circuits for their applications and algorithms, which generally require complicated hardware logic descriptions. Because of the progress made in the FPGA development environment in recent years, the High-Level Synthesis (HLS) development environment using the OpenCL language has become popular. Based on our experience describing kernels using OpenCL, we found that a more aggressive programming strategy is necessary to realize true high performance based on a "codesign" concept to implement the necessary features and operations to fit the target application in an FPGA design. In this paper, we optimize the Authentic Radiation Transfer (ART) method on an FPGA using OpenCL. We also discuss a method to parallelize its computation in an FPGA and a method to optimize the OpenCL code on FPGAs. Using a codesigned method for the optimized programming of a specific application with OpenCL for an FPGA, we achieved a performance that is 6.9 times faster than that of a CPU implementation using OpenMP, and almost the same performance as a GPU implementation using CUDA. The ART code should work on a larger configuration with multiple FPGAs requiring interconnections between them. Considering the current advanced FPGAs with interconnection features, we believe that their parallelized implementation with multiple FPGAs will achieve a higher performance than GPU.