  Although there have been remarkable advances in quantum computing (QC), it
remains crucial to simulate quantum programs using classical large-scale
parallel computing systems to validate quantum algorithms, comprehend the
impact of noise, and develop resilient quantum applications. This is
particularly important for bridging the gap between near-term
noisy-intermediate-scale-quantum (NISQ) computing and future fault-tolerant
quantum computing (FTQC). Nevertheless, current simulation methods either lack
the capability to simulate noise, or simulate with excessive computational
costs, or do not scale out effectively.
  In this paper, we propose TANQ-Sim, a full-scale density matrix based
simulator designed to simulate practical deep circuits with both coherent and
non-coherent noise. To address the significant computational cost associated
with such simulations, we propose a new density-matrix simulation approach that
enables TANQ-Sim to leverage the latest double-precision tensorcores (DPTCs) in
NVIDIA Ampere and Hopper GPUs. To the best of our knowledge, this is the first
application of double-precision tensorcores for non-AI/ML workloads. To
optimize performance, we also propose specific gate fusion techniques for
density matrix simulation. For scaling, we rely on the advanced GPU-side
communication library NVSHMEM and propose effective optimization methods for
enhancing communication efficiency. Evaluations on the NERSC Perlmutter
supercomputer demonstrate the functionality, performance, and scalability of
the simulator. We also present three case studies to showcase the practical
usage of TANQ-Sim, including teleportation, entanglement distillation, and
Ising simulation. TANQ-Sim will be released on GitHub.
