一个软件/硬件并行统一随机数生成框架

Yuan Li, Minxuan Zhang
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引用次数: 0

摘要

本文提出了一种并行生成均匀随机数的软硬件框架。该软件采用快速跳转技术,为每个生成器生成初始状态,以保证不同子流的独立性。在软件的支持下,通过简单地复制单个发生器,可以很容易地构建硬件结构。我们将该框架应用于MT19937算法的并行化。实验结果表明,该框架能够生成任意数量的独立并行随机序列,同时获得与并行核数大致成正比的加速。同时,我们的框架在吞吐量和可扩展性方面都优于现有文献报道的架构。此外,我们在Xilinx Virtex-5 FPGA器件上实现了149个并行MT19937生成器实例。实现了426.1 m采样/s的吞吐量。与CPU和GPU实现相比,吞吐量提高了10.0倍和2.5倍,吞吐量和功率效率分别提高了167.3倍和18.1倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Software/Hardware Parallel Uniform Random Number Generation Framework
In this paper, a software/hardware framework is proposed for generating uniform random numbers in parallel. Using the Fast Jump Ahead technique, the software can produce initial states for each generator to guarantee independence of different sub-streams. With support from the software, the hardware structure can be easily constructed by simply replicating the single generator. We apply the framework to parallelize MT19937 algorithm. Experimental results shows that our framework is capable of generating arbitrary number of independent parallel random sequences while obtaining speedup roughly proportional to the number of parallel cores. Meanwhile, our framework is superior to those existing architectures reported in the literatures in both throughput rate and scalability. Furthermore, we implement 149 parallel instances of MT19937 generators on a Xilinx Virtex-5 FPGA device. It achieves the throughput of 42.61M samples/s. Compared to CPU and GPU implementations, the throughput is 10.0 and 2.5 times faster, while the throughputpower efficiency achieves 167.3 and 18.1 times speedup, respectively.
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