Accelerating Shor's Factorization Algorithm on GPUs

Abstract

Shor's quantum algorithm is very important for cryptography, since it can factor large numbers much faster than classical algorithms. In this study, we implement a simulator for Shor's quantum algorithm on graphic processor units (GPU) and compare our results with Liquid -which is Microsoft quantum simulation platform- and two classical CPU-implementations. We evaluate 10 benchmarks for comparing our GPU implementation with Liquid and single-core implementation. The analysis shows that GPU vector operations is more suitable for Shor's quantum algorithm. Our GPU kernel function is compute-bound, due to all threads in a block reach to the same element of the state vector. Our implementation has $52.5\times$ speedup over single-core algorithm and $20.5\times$ speedup over Liquid.