Low-Level and NUMA-Aware Optimization for High-Performance Quantum Simulation

TL;DR

This paper presents an open-source, NUMA-aware, low-level optimization extension for the QuEST quantum simulator, achieving significant speedups in simulating various quantum algorithms on modern hardware.

Contribution

It introduces a hardware-specific, open-source optimization framework for quantum simulation that enhances performance and scalability on single-node systems.

Findings

Speedups of 5.5-6.5x for single-qubit gates

4.5x acceleration for two-qubit gates

Substantial improvements for quantum algorithms like Grover and Shor

Abstract

Scalable classical simulation of quantum circuits is crucial for advancing quantum algorithm development and validating emerging hardware. This work focuses on performance enhancements through targeted low-level and NUMA-aware tuning on a single-node system, thereby not only advancing the efficiency of classical quantum simulations but also establishing a foundation for scalable, heterogeneous implementations that bridge toward noiseless quantum computing. Although few prior studies have reported similar hardware-level optimizations, such implementations have not been released as open-source software, limiting independent validation and further development. We introduce an open-source, high-performance extension to the QuEST state vector simulator that integrates state-of-the-art low-level and NUMA-aware optimizations for modern processors. Our approach emphasizes locality-aware computation and incorporates hardware-specific techniques including NUMA-aware memory allocation, thread pinning, AVX-512 vectorization, aggressive loop unrolling, and explicit memory prefetching. Experiments demonstrate substantial speedups--5.5-6.5x for single-qubit gate operations, 4.5x for two-qubit gates, 4x for Random Quantum Circuits (RQC), and 1.8x for the Quantum Fourier Transform (QFT). Algorithmic workloads further achieve 4.3-4.6x acceleration for Grover and 2.5x for Shor-like circuits. These results show that systematic, architecture-aware tuning can significantly extend the practical simulation capacity of classical quantum simulators on current hardware.