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"Well, in our country," said Alice, still panting a little, "you'd generally get to somewhere else—if you run very fast for a long time, as we've been doing."

"A slow sort of country!" said the Queen. "Now, here, you see, it takes all the running you can do, to keep in the same place. If you want to get somewhere else, you must run at least twice as fast as that!"

Carroll, Lewis: Through the Looking-Glass, Chapter 2

About

The Red Queen benchmark framework was created to facilitate the benchmarking algorithms used in quantum compilation.

The framework is tightly integrated into pytest. Therefore, to use it effectively, you should know the basics of pytest first. Take a look at the introductory material.

Usage

Red Queen is a framework for benchmarking quantum compilation algorithms. Since it was not designed as a package, there is no notion of installation. Hence, you must clone this repository to use it:

git clone [email protected]:Qiskit/red-queen.git

To run benchmarks, you must first go to the red-queen directory and install the required packages:

cd red-queen
pip install -r requirements.txt

Now, suppose you want to run the mapping benchmarks using only tweedledum. You must do it using pytest

pytest red_queen/games/mapping/map_queko.py -m tweedledum --store

To run pytest on Windows, you will have to use python -m in order to run the pytest command. You will also need to add -s to your pytest call to disable stdin handling.

python -m pytest -s red_queen/games/mapping/map_queko.py -m tweedledum --store

The benchmark suite will consider all functions named bench_* in red_queen/games/mapping/map_queko.py. Because we set the -m option, only the the ones marked with tweedledum will be run. (We could easy do the same for qiskit). If you don't define a -m option, all bench_* functions will be run.

The --store option tells the framework to store the results in json file in the results directory. To see the results as a table, you can use the you can use:

python -m report.console_tables --storage results/0001_bench.json

Warning

This code is still under development. There are many razer sharp edges.

For information of how execution works and other details about the framwork design, see the ARCHITECTURE.md

Acknowledgments

Some design choices made during the development of this framework were based on the knowledge of the internals of the following established pytest plugins:

License

This software is licensed under the Apache 2.0 licence (see LICENSE)

Contributing

If you're interested in contributing to Red Queen please see the contributing guide.