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Implementation of hardware-accelerated scalable parallel random number generators

  • University of Tennessee
  • University of Tennessee

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

The Scalable Parallel Random Number Generators (SPRNGs) library is widely used in computational science applications such as Monte Carlo simulations since SPRNG supports fast, parallel, and scalable random number generation with good statistical properties. In order to accelerate SPRNG, we develop a Hardware-Accelerated version of SPRNG (HASPRNG) on the Xilinx XC2VP50 Field Programmable Gate Arrays (FPGAs) in the Cray XD1 that produces identical results. HASPRNG includes the reconfigurable logic for FPGAs along with a programming interface which performs integer random number generation. To demonstrate HASPRNG for Reconfigurable Computing (RC) applications, we also develop a Monte Carlo -estimator for the Cray XD1. The RC Monte Carlo -estimator shows a 19.1 speedup over the 2.2GHz AMD Opteron processor in the Cray XD1. In this paper we describe the FPGA implementation for HASPRNG and a -estimator example application exploiting the fine-grained parallelism and mathematical properties of the SPRNG algorithm.

Original languageEnglish
Article number930821
JournalVLSI Design
Volume2010
DOIs
StatePublished - 2010

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