This is a mini-benchmarking library for Python that allows you to measure CPU Performance Monitoring Unit (PMU) counters, jemalloc memory allocations, and custom measurements like the number of hash collisions.
- Python 3.6 or higher
- Clone the repository:
git clone https://github.com/athy125/PyPerfMonitor.git
cd PyPerfMonitor
- Create and activate a virtual environment (optional but recommended):
python -m venv venv
source venv/bin/activate # On Windows, use `venv\Scripts\activate`
- Install the required dependencies:
pip install -r requirements.txt
The pmu_benchmark.py file provides functionality to measure CPU PMU counters using the perf library. You can specify the events to measure and the function you want to benchmark.
Example usage:
from pmu_benchmark import PMUBenchmark
def example_function():
for i in range(100000):
_ = i * i
if __name__ == "__main__":
pmu_benchmark = PMUBenchmark(runs=5, number=1000)
pmu_events = [
"cpu/cache-misses/",
"cpu/branch-misses/",
]
pmu_benchmark.measure_pmu_counters(example_function, events=pmu_events)The memory_benchmark.py file provides functionality to measure memory allocations using pyjemalloc. You can specify the allocation size and the number of runs.
Example usage:
from memory_benchmark import MemoryBenchmark
if __name__ == "__main__":
memory_benchmark = MemoryBenchmark(runs=5, number=1000)
allocation_size = 1024
memory_benchmark.measure_memory_allocation(allocation_size)The custom_benchmark.py file allows you to measure custom computations. In this example, we measure the number of hash collisions for a custom function.
Example usage:
def custom_hash_collision():
collisions = 0
hash_set = set()
# Generate 10000 random strings and calculate their SHA-256 hash values
for i in range(10000):
data = ''.join(random.choices(string.ascii_letters + string.digits, k=10)).encode()
hash_value = hashlib.sha256(data).hexdigest()
# Check for hash collisions
if hash_value in hash_set:
collisions += 1
hash_set.add(hash_value)
print(f"Number of hash collisions: {collisions}")If you want to contribute to this project, feel free to create a pull request or submit an issue.
This project is licensed under the MIT License.
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