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A high-performance CUDA library for fused matrix multiplication with ReLU

Project description

🚀 cuMatfuse

cuMatfuse is a minimal CUDA library for fused matrix multiplication with ReLU activation: C = ReLU(A × B)

✨ Features

  • CUDA-accelerated fused GEMM with ReLU
  • Lightweight and portable
  • Easy to extend and integrate into ML inference pipelines

🛠 Requirements

  • NVIDIA GPU (Compute Capability 7.0+)
  • CUDA Toolkit ≥ 11.8
  • CMake ≥ 3.18
  • Linux or Windows

🔧 Build Instructions

git clone https://github.com/divakar-yadav/cuMatfuse.git
cd cuMatfuse
mkdir build && cd build
cmake ..
make

🧪 Run Example

./cuMatfuse_demo

Expected Output:

C = ReLU(A × B):
22 28
49 64
76 100
6 8

📦 License

MIT

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