Using a grid, the system designs a set of rectangular silicon structures filled with tiny pores. The system continually adjusts each pixel in the grid until it arrives at the desired mathematical ...

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 ...

Sparse matrices underpin a vast range of scientific and engineering applications, from finite element analysis and computational fluid dynamics to graph processing and machine learning. By encoding ...

Hand-tuned WebAssembly implementations for efficient execution of web-based sparse computations including Sparse Matrix-Vector Multiplication (SpMV), sparse triangular solve (SpTS) and other useful ...

SpMV-CNN: A set of convolutional neural nets for estimating the run time and energy consumption of the sparse matrix-vector product ...

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Abstract: The rising popularity of deep learning algorithms demands special accelerators for matrix-matrix multiplication. Most of the matrix multipliers are designed based on the systolic array ...