A Hardware-Native Realisation of Semi-Empirical Electronic Structure Theory on Field-Programmable Gate Arrays

TL;DR

This paper demonstrates the first hardware-native implementation of semi-empirical electronic structure methods on FPGA, achieving significant speedup and energy efficiency for quantum-chemical calculations.

Contribution

It introduces a novel FPGA-based design for semi-empirical electronic structure calculations, enabling deterministic, high-throughput computation without host intervention.

Findings

DFTB0 Hamiltonian generator over four times faster than CPU

Deterministic execution on FPGA with streaming dataflow

Potential for further improvements in eigensolvers and capabilities

Abstract

High-throughput quantum-chemical calculations underpin modern molecular modelling, materials discovery, and machine-learning workflows, yet even semi-empirical methods become restrictive when many molecules must be evaluated. Here we report the first hardware-native realisation of semi-empirical electronic structure theory on a field-programmable gate array (FPGA), implementing as a proof of principle Extended H\"uckel Theory (EHT) and non-self-consistent Density Functional Tight Binding (DFTB0). Our design performs Hamiltonian construction and diagonalisation on the FPGA device through a streaming dataflow, enabling deterministic execution without host intervention. On a mid-range Artix-7 FPGA, the DFTB0 Hamiltonian generator delivers a throughput over fourfold higher than that of a contemporary server-class CPU. Improvements in eigensolver design, memory capacity, and extensions to nuclear gradients and excited states could further expand capability. Combined with the inherent energy efficiency of FPGA dataflow, this work opens a pathway towards sustainable, hardware-native acceleration of electronic-structure simulation and direct hardware implementations of a broad class of methods.