CAMPIE 🥧

Python APIs to simulate various CAMs (Content Addressable Memory) on GPUs at scale.

• Installation
• Example
• Documentation
• Examples
• Contributing
• License

Overview

CAMPIE is a utility library that builds on top of NumPy and CuPy for fast and efficient simulation of CAM hardwares on CUDA GPUs.
It implements custom CUDA kernels for ACAM (Analog CAM) and TCAM (Ternary Cam) simulation and adjacent utility functionality accessible under a simple Python API.

Installation

CAMPIE uses CuPy under the hood, which requires you to install a different package based on your CUDA version if you are using pip.

The CUDA version that you are installing CAMPIE for is specified as an extra like below:

pip install campie[cu11x]

for Poetry, this would be:

poetry add -E cu11x campie

The available CUDA version extras are as follows: cu110, cu111, cu11x, cu12x. You should only ever install one CUDA extra or you will cause conflicts.

For more context, see the CuPy installation instructions and the pyproject.toml.

Example

import campie
import numpy as np

x = np.nan  # nan = don't care

# cam_rows x columns
cam = np.array([
  [0, 0, 1, 0],
  [1, 1, x, 0],
  [0, 0, 0, 0],
  [x, x, 0, 0],
  [0, 0, 1, 1],
])

# input_rows x columns
inputs = np.array([
  [0, 0, 0, 0],
  [0, 1, 0, 0],
  [1, 1, 1, 0],
]).astype(np.float64)

# this runs on the GPU, `matches` is still in GPU memory
matches = campie.tcam_match(inputs, cam)
print(matches)

# -> input_rows x cam_rows
array([
  [0, 0, 1, 1, 0],  # input 1 matches cam rows 3 and 4
  [0, 0, 0, 1, 0],  # input 2 matches cam row 4
  [0, 1, 0, 0, 0],  # input 3 matches cam row 2
])

For detailed information on all available APIs, visit the documentation. Alternatively, see the example notebook for a practical introduction.

Contributing

In order for us to accept your pull request, you will need to sign-off your commit. This page contains more information about it. In short, please add the following line at the end of your commit message:

Signed-off-by: First Second <email>

Dependency Management

Python dependencies are managed via Poetry:

poetry install -E cu11x

Poetry is also used to publish the library to PyPI:

poetry build
poetry publish

Formatting & Linting

CAMPIE uses ruff to format and lint Python source code.

To format all Python files:

ruff --fix .

Reference Generation

scripts/gen_reference.py is used to extract doc comments from the source code and generates docs/reference.md.

To regenerate the reference:

# installed into the virtual environment by poetry
gen-reference

# or alternatively
python scripts/gen_reference.py

License

CAMPIE is licensed under the Apache 2.0 license.