Field Programmable Gate Arrays (FPGAs) for Enhancing the Speed and Energy Efficiency of Quantum Dynamics Simulations

13 March 2020, Version 1
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

We present the first application of field programmable gate arrays (FPGAs) as new, customizable hardware architectures that can be harnessed for the fast and energy-efficient calculation of quantum dynamics simulations of large chemical/material systems. Instead of tailoring the software to fixed hardware (which is the typical case for writing quantum chemistry code for CPUs/GPUs), FPGAs allow us to directly customize the underlying hardware - even at the level of specific electrical signals in the circuit - to give a truly optimized computational performance for complex quantum dynamics calculations. By offloading the most intensive and repetitive calculations onto an FPGA, we show that the computational performance of our hardware implementation for real-time electron dynamics calculations can even exceed that of optimized commercial mathematical libraries running on high-performance GPUs. In addition to this impressive computational speedup, we show that FPGAs are immensely energy-efficient and consume 4 times less energy than modern GPU or CPU architectures. These energy savings are a practical and important metric for supercomputing centers (several of which exceed over $1 million in power costs alone), as exascale computing capabilities become more widespread and commonplace. Taken together, the implementation techniques and performance metrics of our study demonstrate that FPGAs could play a promising role in upcoming quantum chemistry and materials science applications, particularly for the acceleration and energy-efficient execution of quantum dynamics calculations.

Keywords

quantum chemistry
quantum dynamics
FPGA
FPGA Designs
GPU
GPU computing
Real-Time Time-Dependent Density Functional Theory
fast algorithms
energy-efficient
Supercomputing
Density Functional Tight Binding
Computational Chemistry
Electron Dynamics
customizable hardware

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