Performance benchmarks of quantum simulators

There has been a rapid rise in the development of quantum simulators, both to validate the quantum hardware and also to explore the limitations of classical simulation, thereby the regime of quantum advantage. Quantum simulators which are HPC (High Performance Computing) compliant are chosen and their performance is benchmarked on various compute capabilities as offered by the HPC.

Notebooks provide the Time to Solution (TtS) performance of the quantum simulators obtained using a containerized toolchain wherein each simulation package accepts the quantum algorithm in the QASM2 format, the simulation package and the compute capability on the HPC. The containerized toolchain allows for portability of the benchmarking scheme, reproducibility of the performance data, is modular and easily extensible to include other packages.

The benchmarked packages include:
# Package Language Singlethread Multithread GPU MPI Multi-GPU
Single Precision Double Precision Single Precision Double Precision Single Precision Double Precision Single Precision Double Precision
1 Qiskit Python
2 Cirq Python
3 Qsimcirq Python
4 Pennylane Python
5 Pennylane-lightning C++
6 Qibo Python
7 Qibojit Python
8 Yao Julia
9 Quest C
10 Qulacs Python
11 Intel-QS C++
12 Projectq Python
13 Qcgpu Python
14 HiQ Python
15 Hybridq Python
16 SV-Sim Python
17 Qrack C++
18 Qpanda Python
19 CuQuantum Python
20 myQLM (py) Python
21 myQLM (C++) C++
22 Braket Python
23 Q++ C++
The quantum algorithms benchmarked include: