QTensor: Parallel Quantum Circuit Simulator

ORAL

Abstract

We present a parallel quantum circuit simulator* designed to run on large supercomputers with the eventual goal to run at scale on exa-scale supercomputers Aurora and Frontier. The simulator is based on the tensor network representation of quantum circuits. We proposed a novel parallelization strategy that is based on the splitting of the partially contracted tensor expression. The resulting slices of the tensor expression had significantly smaller memory footprints which allowed us to contract partial tensor networks on individual MPI ranks. We will discuss the performance considerations of working with tensor networks at scale and demonstrate the efficiency of QAOA simulation in a hybrid GPU-CPU environment using both Xeon Phi and Nvidia GPUs, on circuits with over a large number of qubits.

*QTensor code is publicity available at https://github.com/danlkv/QTensor

*This research is supported by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Materials Sciences and Engineering Division, and by the Exascale Computing Project (17-SC-20-SC), This material is based upon work supported by the Defense Advanced Research Projects Agency (DARPA) under Contract No. HR001120C0068.

Presenters

  • Yuri Alexeev

    • Argonne National Laboratory

Authors

  • Yuri Alexeev

    • Argonne National Laboratory
  • Danylo Lykov

    • Argonne National Laboratory
    • Northern Illinois University
  • Cameron Ibrahim

    • Argonne National Laboratory
  • Alexey Galda

    • University of Chicago
    • James Franck Institute, University of Chicago