Im2col SIMD for 2D Tensors

A SIMD-optimized implementation of the im2col operation for 2D images (e.g., grayscale). This repository provides C++ source code targeting AVX2 (x86_64) and NEON (Armv8) architectures, as well as a reference (non-SIMD) implementation. You can integrate the resulting library into your own C++ project or access it from Python through a simple Ctypes wrapper.

Overview

The im2col (“image to column”) operation is commonly used in convolutional neural networks (CNNs) to transform a 2D image (or feature map) into a set of column vectors, facilitating efficient matrix-multiplication-based convolutions.

By taking advantage of SIMD intrinsics, we can significantly speed up the im2col computation on CPUs that support vector operations. This repository includes:

• AVX2 implementation for modern x86_64 processors
• NEON implementation for Armv8 processors
• Reference scalar implementation (no intrinsics) for portability or as a fallback

The repository also contains a Python wrapper and a Jupyter Notebook that can be used as an example on how to use the library in Python.

Installation

1. Clone this repository:

   git clone https://github.com/Henvezz95/im2col_2D.git
   cd im2col_2D

2. Configure and build with CMake:

    mkdir build && cd build
    cmake -DCMAKE_BUILD_TYPE=Release ..
    cmake --build .

   CMake will detect your CPU architecture and automatically compile the corresponding SIMD implementation (AVX2, NEON, or reference).

3. After building, you should find a shared library (e.g., libim2col.so on Linux or im2col.dll on Windows) in your build folder.

Folder Structure

 im2col_2D/
 ├── CMakeLists.txt        # Main CMake build script
 ├── src/
 │   ├── im2col_AVX2.cpp   # AVX2 implementation
 │   ├── im2col_NEON.cpp   # NEON implementation
 │   └── im2col_ref.cpp    # Reference (fallback) implementation
 ├── python/
 │   └── im2col.py         # Python ctypes wrapper
 ├── Test Notebook.ipynb   # Jupyter Notebook example