HQ-Sim: High-performance State Vector Simulation of Quantum Circuits on Heterogeneous HPC Systems

Quantum circuit simulations are applied in more and more circumstances as the quantum computing community becomes broader. It helps researchers to evaluate the quantum algorithms and relieve the burden of limited quantum computing resources. However, most of the state-of-the-art quantum simulators utilizes either CPU or GPU to store and calculate the state vector, which results in resources stravation. Morever, the mamximum number of qubits supported by simulator is bounded by the memory, since the memory utilization increases exponentially with the number of qubits. In this study, we leverage Heterogeneous computing to utilize both CPU and GPU to store and update state vectors. We also integrate lossy data compression to reduce memory requirements. Specifically, we develop a heterogeous framework that has a dynamic scheduler to fully utilize the computing resources. We apply lossy compression to chunked state vector to make the maximum number of qubits higher than the regular simulators, the compression also benifits the data movement between CPU and GPU.

随着量子计算社区变得更广泛，量子电路模拟将在越来越多的情况下应用。它可以帮助研究人员评估量子算法并减轻有限的量子计算资源的负担。但是，大多数最先进的量子模拟器都利用CPU或GPU来存储和计算状态向量，从而导致资源储备。此外，由于内存利用率随量子数的数量而呈指数增加，因此模拟器支持的MAMXimum数量是由内存界定的。在这项研究中，我们利用异质计算利用CPU和GPU来存储和更新状态向量。我们还集成了有损耗的数据压缩以减少内存需求。具体来说，我们开发了一个杂色框架，该框架具有一个动态调度程序，可以充分利用计算资源。我们对块状状态矢量进行有损压缩，以使最大Qubit数量高于常规模拟器，该压缩还可以利用CPU和GPU之间的数据运动。