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qstone
Advanced tools
A utility to benchmark the quality of HPC and Quantum Computer integration.
QStone allows you to define a set of users for which configurable quantum applications will be randomly selected and executed. The benchmark generates different portable files (.tar.gz), each supporting different users and schedulers.
Currently supported quantum applications:
Key features:
The benchmark operates under specific assumptions.
Building appropriate hardware/software infrastructure for HPCQC requires significant effort. QStone enables a data-driven approach where you can measure performance, implement fixes, and measure again with every new version of quantum computers, software, and HPC hardware.
| Platform | Architecture | OS |
|---|---|---|
| Apple Silicon | M1-M4 | macOS |
| Intel | x86_64 | Ubuntu |
| IBM Power | Power9 | RedHat |
Python versions: 3.10 - 3.12
pip install QStone
First, install OpenMPI:
# Ubuntu/Debian
sudo apt install openmpi-bin openmpi-common libopenmpi-dev
# RedHat/CentOS/Fedora
sudo yum install openmpi openmpi-devel
# macOS
brew install openmpi
Then install QStone with MPI support:
pip install QStone[mpi]
qstone generate -i config.json [--atomic/-a] [--scheduler/-s "slurm"/"jsrun"/"bare_metal"]
Options:
--atomic / -a: Generate single-step jobs instead of three-phase jobs (pre/run/post)--scheduler / -s: Select output scheduler (default: bare_metal)Supported schedulers: bare metal, Altair/FNC, SLURM/SchedMD
qstone run -i scheduler.qstone.tar.gz [-o output_folder]
Alternative: Extract the tar.gz file and run manually:
tar -xzf scheduler.qstone.tar.gz
cd qstone_suite
sh qstone.sh
Single user:
qstone profile --cfg config.json --folder qstone_profile
Multiple users:
qstone profile --cfg config.json --folder qstone_profile --folder qstone_profile2
Create a config.json file with the following structure:
{
"environment": {
"project_name": "my_quantum_project",
"scheduling_mode": "LOCK",
"job_count": 5,
"qpu": {
"mode": "RANDOM"
},
"connectivity": {
"mode": "NO_LINK",
"qpu": {
"ip_address": "0.0.0.0",
"port": 55
}
},
"timeouts": {
"http": 5,
"lock": 4
}
},
"jobs": [
{
"type": "VQE",
"qubits": [4, 6],
"num_shots": [100, 200],
"walltime": 10,
"nthreads": 4,
"app_logging_level": 2
},
{
"type": "RB",
"qubits": [2],
"num_shots": [100],
"walltime": 10,
"nthreads": 2
},
{
"type": "QBC",
"qubits": [4],
"num_shots": [32],
"walltime": 20,
"nthreads": 2
}
],
"users": [
{
"user": "user0",
"computations": {
"VQE": 0.05,
"RB": 0.94,
"PyMatching": 0.01
}
}
]
}
For detailed configuration options, refer to the JSON schema.
Note: Only SLURM currently supports the high-performance "SCHEDULER" mode with lowest latency. See SLURM documentation for more details.
from qstone.generators import generator
def main():
generator.generate_suite(
config="config.json",
job_count=100,
output_folder=".",
atomic=False,
scheduler="bare_metal"
)
if __name__ == "__main__":
main()
For questions, issues, or feature requests, please visit our GitHub repository or open an issue.
FAQs
Benchmarking suite for Quantum Computers integration into HPC Systems
We found that qstone demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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