Early but promising results in quantum computing have been enabled by the concurrent development of quantum algorithms, devices, and materials. Classical simulation of quantum programs has enabled the design and analysis of algorithms and implementation strategies targeting current and anticipated quantum device architectures. In this work, we present a graph-based approach to achieving efficient quantum circuit simulation. Our approach involves partitioning the graph representation of a given quantum circuit into acyclic sub-graphs/circuits that exhibit better data locality. Simulation of each sub-circuit is organized hierarchically, with the iterative construction and simulation of smaller state vectors, improving overall performance. Also, this partitioning reduces the number of passes through data, improving the total computation time. We present three partitioning strategies and observe that acyclic graph partitioning typically results in the best time-to-solution. In contrast, other strategies reduce the partitioning time at the expense of potentially increased simulation times. Experimental evaluation demonstrates the effectiveness of our approach.
The simulator consists of two components: The circuit partitioning module and the hierarchical state vector simulator. The simulator accepts acyclic partitions of an input circuit and the circuit partitioning module partitions an input circuit, given as in dot format, into acyclic blocks.
This work is a collaboration between Pacific Northwest National Laboratory (PNNL) and TDALab.
If you use HiSVSIM, please cite: Partitioning Module:
HiSVSIM-dagP (Latest, Sep 7,2022)
Dataset:
dataset (Latest, Sep 7, 2022)
Simulation Module:
Coming Soon