Sparse matrix-matrix multiplication (SpMM) is a crucial kernel in various applications, including sparse deep neural networks [1]–[6], graph analytics [7], triangle counting [8], and linear algebra ...

MIT researchers have designed silicon structures that can perform calculations in an electronic device using excess heat instead of electricity. These tiny structures could someday enable more ...

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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 ...

Samuel is Collider's List Flex Editor (previously Lead List Editor), which means he's pretty much always hovering around Collider's List department. A writing and editing automaton based in Nashville, ...

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 ...

When you watch “The Matrix” at Cosm, you’re essentially seeing a film within a film. A shot inside an apartment becomes a glimpse into an entire complex. A fight scene on a rooftop is now one small ...

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 ...