Abstract: Distributed computations, such as distributed matrix multiplication, can be vulnerable to significant security issues, notably Byzantine attacks. These attacks may target either worker nodes ...

This paper came across my feed that implements sparse matrix-vector multiplication. Sparse matrix-vector multiplication (SpMV) is a fundamental operation in scientific computing, data analysis, and ...

Performing dense*sparse matrix multiplication using a CuSparseMatrixCOO does not yield the correct result. In the example below, dense*sparse spmm is performed correctly when using a CuSparseMatrixCSC ...

You can now order an “Iron Dome” for mosquitoes. Its name is the Photon Matrix, a black box about the size of a smartphone that can detect, track, and eliminate mosquitoes mid-flight using an ...

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Dozens of machine learning algorithms require computing the inverse of a matrix. Computing a matrix inverse is conceptually easy, but implementation is one of the most challenging tasks in numerical ...

Discovering faster algorithms for matrix multiplication remains a key pursuit in computer science and numerical linear algebra. Since the pioneering contributions of Strassen and Winograd in the late ...