Design decisions in the pipelined architecture for Quantum Monte Carlo simulations

Abstract

The ground-state properties of atomic and molecular clusters can be obtained using Quantum Monte Carlo (QMC) simulations. We propose a reconfigurable hardware architecture using Field-Programmable Gate Arrays (FPGAs) to implement the kernels of the QMC application. To achieve higher clock rates, we experiment with different pipeline stages for each component of the design and develop a deeply pipelined architecture that provides the best performance in terms of clock rate, while at the same time has a modest use of embedded memory and multiplier resources so we can fit additional functions in a future implementation. Here, we discuss the details of the pipelined architecture and our design decisions while developing a general framework that can be used to obtain the potential energy of atomic or molecular clusters and extended to compute other useful properties.