Floppy Documentation¶

Welcome to the Floppy documentation!

Floppy is a framework for analyzing and counting floating-point operations (FLOPs) in Python code, with special focus on numerical computations using NumPy.

Features¶

Runtime FLOP Counting: Track FLOPs in your code as it executes
Transparent array operation tracking
Support for high-level NumPy operations
Thread-safe operation
Selective monitoring of code paths
Static Analysis: Analyze potential FLOP operations in your codebase
Identify potential FLOP-contributing functions
Get insights before execution

Installation¶

For monty_lab conda environment, please follow instructions from Thousand Brains Project documentation and run:

conda create --clone tbp.monty -n monty_lab
conda activate monty_lab
cd path/to/monty_lab/floppy
pip install -e .

Quick Start¶

from floppy.counting.base import FlopCounter

with FlopCounter() as counter:
    result = np.matmul(a, b)
    print(f"FLOPs: {counter.flops}")

For analyzing an entire codebase:

python run_static_analysis.py --dir path/to/analyze

Documentation¶

Contributing¶

Contributions are welcome! Please follow the Thousand Brains Project Contributing Guide.

License¶

The MIT License. See the LICENSE for details.