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FPGA acceleration of a quantum Monte Carlo application
Parallel Computing (2008)
  • Robert Hinde, University of Tennessee

Quantum Monte Carlo methods enable us to determine the ground-state properties of atomic or molecular clusters. Here, we present a reconfigurable computing architecture using Field Programmable Gate Arrays (FPGAs) to accelerate two computationally intensive kernels of a Quantum Monte Carlo (QMC) application applied to N-body systems. We focus on two key kernels of the QMC application: acceleration of potential energy and wave function calculations. We compare the performance of our application on two reconfigurable platforms. Firstly, we use a dual-processor 2.4 GHz Intel Xeon augmented with two reconfigurable development boards consisting of Xilinx Virtex-II Pro FPGAs. Using this platform, we achieve a speedup of 3 over a software-only implementation. Following this, the chemistry application is ported to the Cray XD1 supercomputer equipped with Xilinx Virtex-II Pro and Virtex-4 FPGAs. The hardware-accelerated application on one node of the high performance system equipped with a single Virtex-4 FPGA yields a speedup of approximately 25 over the serial reference code running on one node of the dual-processor dual-core 2.2 GHz AMD Opteron. This speedup is mainly attributed to the use of pipelining, the use of fixedpoint arithmetic for all calculations and the fine-grained parallelism using FPGAs. We can further enhance the performance by operating multiple instances of our design in parallel.

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Robert Hinde. "FPGA acceleration of a quantum Monte Carlo application" Parallel Computing Vol. 34 (2008)
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