Showing 2 open source projects for "sparse matrices"

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  • 1
    BlockSparse

    BlockSparse

    Efficient GPU kernels for block-sparse matrix multiplication

    The blocksparse repository provides efficient GPU kernels (TensorFlow custom ops) for block-sparse matrix multiplication and convolution operations. The idea is to exploit block-level sparsity — i.e. treat matrices or weight tensors as composed of blocks, many of which may be zero or unused — to save compute and memory when sparsity patterns are structured. This is particularly useful in models like Sparse Transformers, where attention matrices or intermediate layers may adopt block-sparse patterns to scale better. ...
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  • 2

    ViennaCLBench

    OpenCL linear algebra benchmark GUI for CPUs, GPUs, and MIC

    ViennaCLBench provides a graphical user interface for collecting benchmark data for common OpenCL-accelerated linear algebra operations as implemented in the linear algebra library ViennaCL.
    Downloads: 0 This Week
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