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IEEE Access, 2020 Matrix computing is a basic operational model that was broadly used in science and engineering applications. In this study, we first propose a novel optimization method to obtain a high-performance and scalable architecture for matrix multiplication ...
Longlong Zhang +3 more
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A Systematic Survey of General Sparse Matrix-matrix Multiplication [PDF]
ACM Computing Surveys, 2020 General Sparse Matrix-Matrix Multiplication (SpGEMM) has attracted much attention from researchers in graph analyzing, scientific computing, and deep learning.
Jianhua Gao +3 more
semanticscholar +1 more source
Faster Algorithms for Rectangular Matrix Multiplication [PDF]
, 2012 Let {\alpha} be the maximal value such that the product of an n x n^{\alpha} matrix by an n^{\alpha} x n matrix can be computed with n^{2+o(1)} arithmetic operations.
Gall, François Le
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Accelerating Batched Matrix Multiplication for Variable Small Sizes Based on TVM andApplications [PDF]
Jisuanji kexueIn many practical applications,efficient computation of a large amount of small matrix products across different dimensions is required.For instance,in graph classification tasks based on graph neural networks,multiple adjacency matrices need to be ...
DAI Hanwen, CHEN Changbo
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The border support rank of two-by-two matrix multiplication is seven [PDF]
, 2017 We show that the border support rank of the tensor corresponding to two-by-two matrix multiplication is seven over the complex numbers. We do this by constructing two polynomials that vanish on all complex tensors with format four-by-four-by-four and ...
Bläser, Markus +2 more
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Fully reconfigurable coherent optical vector-matrix multiplication. [PDF]
Optics Letters, 2020 Optics is a promising platform in which to help realize the next generation of fast, parallel, and energy-efficient computation. We demonstrate a reconfigurable free-space optical multiplier that is capable of over 3000 computations in parallel, using ...
James Spall +3 more
semanticscholar +1 more source
A practical streaming approximate matrix multiplication algorithm
Journal of King Saud University: Computer and Information Sciences, 2022 Approximate Matrix Multiplication (AMM) has emerged as a useful and computationally inexpensive substitute for actual multiplication of large matrices. Randomized as well as deterministic solutions to AMM were provided in the past.
Deena P. Francis, Kumudha Raimond
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Matrix black box algorithms - a survey [PDF]
Bulletin of the Polish Academy of Sciences: Technical Sciences, 2022 The implementations of matrix multiplication on contemporary, vector-oriented, and multicore-oriented computer hardware are very carefully designed and optimized with respect to their efficiency, due to the essential significance of that operation in ...
Jerzy Respondek
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Fast Matrix Multiplication [PDF]
Proceedings of the forty-seventh annual ACM symposium on Theory of Computing, 2015 Until a few years ago, the fastest known matrix multiplication algorithm, due to Coppersmith and Winograd (1990), ran in time O(n2.3755). Recently, a surge of activity by Stothers, Vassilevska-Williams, and Le~Gall has led to an improved algorithm running in time O(n2.3729).
Andris Ambainis +2 more
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Cogent Engineering, 2017 Matrix Multiplication is a basic engineering and scientific problem, which has application in various domains. There exists many cryptographic solutions for secure computation of matrix multiplication, but cryptographic preamble makes them infeasible for
Malay Kumar, Jasraj Meena, Manu Vardhan
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