Communication Optimizations for State-vector Quantum Simulator on CPU plus GPU Clusters

Simulating the behavior of quantum circuits on classical computers are one of the widely used approaches for current quantum computing device and quantum algorithm research. State-vector simulators keep all the quantum states in main memory, thus consuming a large amount of memory and resulting in great memory access and communication overhead far longer than calculation time. Many classical simulators, such as QuEST, are designed by serial execution of quantum gates without using the data locality, and all amplitudes need to be exchanged. Such a gate-unaware full data communication scheme forces powerful computation such as GPUs to spend a lot of time on waiting for data transmission. In this paper, we propose a gate-aware on-demand communication quantum simulation framework to optimize communication overhead. A quantum circuit partition method through gate fusion is first proposed to avoid unnecessary communications. Moreover, a on-demand data communication scheme is proposed to optimize data transfer among computation nodes. Based on these designs, a prototype has been implemented on QuEST. We evaluated on an 8-node cluster with four NVIDIA Tesla V100 GPUs on each node and our designs can achieve 3.0x-15.6x speedup compared to QuEST for 32-34-qubit quantum systems. Moverover, it can scale to simulate 37-qubit quantum system instead of 34-qubit quantum system for QuEST.