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Benchmark codes for Qulacs

Source codes for benchmarking the execution times of 10-layer random circuits with several numbers of qubits.

This repository shows a compoarison between Qulacs and several popular existing quantum circuit simulators that have the interfaces of Python or Julia and support simulation with double-precision.

Times are measured with single-thread, multi-thread, and GPU acceralation. If an option of circuit optimization such as gate fusion is provided, we check times with and without circuit optimization.

The benchmark codes are created based on the benchmark project by Roger-luo.

The versions of installed libraries and relevant information are listed in the text files at systeminfo. The benchmark codes are saved in benchmark folder. The results are plotted in image folder by plot.py.

Versions

CPU Benchmark environment

Name Version Note
OS CentOS7
CPU Xeon CPU E5-2687W v4 @ 3.00GHz x 2 Hyperthreading is disabled
GCC 9.2.0
Python 3.7.9
NumPy 1.19.2 Backend is MKL 2020.2
Julia 1.5.2

GPU Benchmark environment

Name Version Note
OS CentOS7
CPU Xeon Silver 4108 CPU @ 1.80 GHz x 2 Hyperthreading is disabled
GPU Tesla V100 PCIe 32GB
GCC 7.3.0
CUDA 10.2
Python 3.7.9
NumPy 1.19.2 Backend is MKL 2020.2
Julia 1.5.2

Libraries

Name Version Note
Intel-QS latest master Installed with DIqsNative=ON
ProjectQ 0.5.1
PyQuEST-cffi 3.2.3.1
Qibo 0.1.2
Qiskit-Aer(-gpu) 0.7.1 Time for backend._controller(qobj) is evaluated
Qulacs 0.2.0
qxelarator 0.3.0
Yao 0.6.3

Requirement

You need to install pytest and pytest-benchmark via pip

Result

Single thread

Single thread results Single thread ratio

Multi thread (24 cores)

Mutli-thread results Multi-thread ratio

GPU acceralation

GPU results GPU ratio

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