Abstract: Efficient representation of sparse matrices is critical for reducing memory usage and improving performance in hardware-accelerated computing systems. This letter presents memory-efficient ...
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The issue is not present in standard pre-built LibTorch package. We had to compile Libtorch 2.8.0 from source, since CUDA support for sparse CSR tensor is in beta and not part of official distribution ...
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The minimal reproducible code is described below. Consider a standard autocast training framework, where a weight matrix is a learnable parameter stored in float type; and input is a sparse_csr ...