Results 21 to 30 of about 43,136 (260)
Hierarchical Coded Matrix Multiplication [PDF]
IEEE Transactions on Information Theory, 2019 In distributed computing systems slow working nodes, known as stragglers, can greatly extend finishing times. Coded computing is a technique that enables straggler-resistant computation. Most coded computing techniques presented to date provide robustness by ensuring that the time to finish depends only on a set of the fastest nodes.
Shahrzad Kiani +2 more
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Fast Sparse Matrix Multiplication [PDF]
ACM Transactions on Algorithms, 2004 Let A and B two n × n matrices over a ring R (e.g., the reals or the integers) each containing at most m nonzero elements. We present a new algorithm that multiplies A and
Raphael Yuster, Uri Zwick
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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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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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Development an Analytical Performance Models for Matrix Multiplication on Distributing Systems [PDF]
IJCI International Journal of Computers and Information, 2009 In this paper, we suggest a mechanism for implementing a distributed application using RMI based on JAVA threads. The application is parallel matrices multiplication depending on distributed the products block of rows and columns on different machines ...
Arabi Keshk
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A New Parallel Matrix Multiplication Method Adapted on Fibonacci Hypercube Structure [PDF]
Journal of Sciences, Islamic Republic of Iran, 2010 The objective of this study was to develop a new optimal parallel algorithm for matrix multiplication which could run on a Fibonacci Hypercube structure. Most of the popular algorithms for parallel matrix multiplication can not run on Fibonacci Hypercube
L Jokar
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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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Multiplication of medium-density matrices using TensorFlow on multicore CPUs
Tehnički Glasnik, 2019 Matrix multiplication is an essential part of many applications, such as linear algebra, image processing and machine learning. One platform used in such applications is TensorFlow, which is a machine learning library whose structure is based on dataflow
Siraphob Theeracheep +1 more
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Communications Faculty Of Science University of Ankara Series A1Mathematics and Statistics, 2017 In this paper, a new matrix multiplication is defined in Rm;nRn;pby using scalar product in Rn, where Rm;nis set of matrices of m rows and n columns. With this multiplication it has been shown that Rn;nis an algebra with unit. By considering this new multiplication we define eigenvalues and eigen vectors of square n n matrix A and also present some ...
KEÇİLİOĞLU, Osman, GÜNDOĞAN, Halit
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On generalized corners and matrix multiplication
CoRR, 2023 Suppose that $S \subseteq [n]^2$ contains no three points of the form $(x,y), (x,y+δ), (x+δ,y')$, where $δ\neq 0$. How big can $S$ be? Trivially, $n \le |S| \le n^2$. Slight improvements on these bounds are obtained from Shkredov's upper bound for the corners problem [Shk06], which shows that $|S| \le O(n^2/(\log \log n)^c)$ for some small $c > 0 ...
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