BGEMM-CUDA is a CUDA-based low-bit GEMM kernel library for efficient neural network inference. It implements optimized binary and ternary matrix multiplication primitives, including binary-weight and ternary-activation computation, with PyTorch extension support for model-level integration.
☆20Aug 30, 2024Updated last year
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