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Accelerators for sparse matrix multiplication are important components in emerging systems. In this paper, we study the main challenges of accelerating Sparse Matrix Multiplication (SpMM). For the situations that data is not stored in the…

Hardware Architecture · Computer Science 2019-06-04 Pareesa Ameneh Golnari , Sharad Malik

We consider the famous Strassen algorithm for fast multiplication of matrices. We show that this algorithm has a nontrivial finite group of automorphisms of order 36 (namely the direct product of two copies of the symmetric group on 3…

Computational Complexity · Computer Science 2014-08-28 Vladimir P. Burichenko

We construct a Neural Network that approximates the matrix multiplication operator for any activation function such that there exists a Neural Network which can approximate the scalar multiplication function. In particular, we use the…

Numerical Analysis · Mathematics 2026-02-06 Gonzalo Romera , Jon Asier Bárcena-Petisco

We propose several new schedules for Strassen-Winograd's matrix multiplication algorithm, they reduce the extra memory allocation requirements by three different means: by introducing a few pre-additions, by overwriting the input matrices,…

Mathematical Software · Computer Science 2009-05-18 Brice Boyer , Jean-Guillaume Dumas , Clément Pernet , Wei Zhou

A tight $\Omega((n/\sqrt{M})^{\log_2 7}M)$ lower bound is derived on the \io complexity of Strassen's algorithm to multiply two $n \times n$ matrices, in a two-level storage hierarchy with $M$ words of fast memory. A proof technique is…

Data Structures and Algorithms · Computer Science 2016-05-10 Gianfranco Bilardi , Lorenzo De Stefani

In 1969, Strassen shocked the world by showing that two n x n matrices could be multiplied in time asymptotically less than $O(n^3)$. While the recursive construction in his algorithm is very clear, the key gain was made by showing that 2 x…

Data Structures and Algorithms · Computer Science 2017-09-01 Joshua A. Grochow , Cristopher Moore

It is well known that Strassen and Winograd algorithms can reduce the computational costs associated with dense matrix multiplication. We have already shown that they are also very effective for software-based multiple precision…

Numerical Analysis · Mathematics 2016-05-16 Tomonori Kouya

We design and develop a work-efficient multithreaded algorithm for sparse matrix-sparse vector multiplication (SpMSpV) where the matrix, the input vector, and the output vector are all sparse. SpMSpV is an important primitive in the…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-10-26 Ariful Azad , Aydin Buluc

We give two algorithms for output-sparse matrix multiplication (OSMM), the problem of multiplying two $n \times n$ matrices $A, B$ when their product $AB$ is promised to have at most $O(n^{\delta})$ many non-zero entries for a given value…

Data Structures and Algorithms · Computer Science 2025-08-15 Huck Bennett , Karthik Gajulapalli , Alexander Golovnev , Evelyn Warton

This paper considers the problem of outsourcing the multiplication of two private and sparse matrices to untrusted workers. Secret sharing schemes can be used to tolerate stragglers and guarantee information-theoretic privacy of the…

Information Theory · Computer Science 2023-06-28 Maximilian Egger , Marvin Xhemrishi , Antonia Wachter-Zeh , Rawad Bitar

Variational formulations of reconstruction in computed tomography have the notable drawback of requiring repeated evaluations of both the forward Radon transform and either its adjoint or an approximate inverse transform which are…

Numerical Analysis · Mathematics 2017-05-23 Richard C. Barnard , Rick Archibald

We present the submatrix method, a highly parallelizable method for the approximate calculation of inverse p-th roots of large sparse symmetric matrices which are required in different scientific applications. We follow the idea of…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-03-06 Michael Lass , Stephan Mohr , Hendrik Wiebeler , Thomas D. Kühne , Christian Plessl

The quest for non-commutative matrix multiplication algorithms in small dimensions has seen a lot of recent improvements recently. In particular, the number of scalar multiplications required to multiply two $4\times4$ matrices was first…

Symbolic Computation · Computer Science 2025-11-27 Jean-Guillaume Dumas , Clément Pernet , Alexandre Sedoglavic

Symmetric Nonnegative Matrix Factorization (SNMF) models arise naturally as simple reformulations of many standard clustering algorithms including the popular spectral clustering method. Recent work has demonstrated that an elementary…

Computer Vision and Pattern Recognition · Computer Science 2016-09-20 Reza Borhani , Jeremy Watt , Aggelos Katsaggelos

A parallel algorithm has perfect strong scaling if its running time on P processors is linear in 1/P, including all communication costs. Distributed-memory parallel algorithms for matrix multiplication with perfect strong scaling have only…

Data Structures and Algorithms · Computer Science 2012-02-16 Grey Ballard , James Demmel , Olga Holtz , Benjamin Lipshitz , Oded Schwartz

This paper investigates the problem of Secure Multi-party Batch Matrix Multiplication (SMBMM), where a user aims to compute the pairwise products…

Information Theory · Computer Science 2021-07-21 Jinbao Zhu , Qifa Yan , Xiaohu Tang

We study the problem of computing matrix chain multiplications in a distributed computing cluster. In such systems, performance is often limited by the straggler problem, where the slowest worker dominates the overall computation latency.…

Information Theory · Computer Science 2026-01-14 Jesús Gómez-Vilardebò

To multiply astronomic matrices using parallel workers subject to straggling, we recommend interleaving checksums with some fast matrix multiplication algorithms. Nesting the parity-checked algorithms, we weave a product code flavor…

Information Theory · Computer Science 2022-01-13 Hsin-Po Wang , Iwan Duursma

In 1969 Strassen showed surprisingly that it is possible to multiply two 2 x 2 matrices using seven multiplications and 18 additions, instead of the naive eight multiplications and four additions. The number of additions was later reduced…

Symbolic Computation · Computer Science 2026-01-12 Erik Mårtensson , Paul Stankovski Wagner , Joshua Stapleton

In this work the algorithms of fast multiplication of matrices are considered. To any algorithm there associated a certain group of automorphisms. These automorphism groups are found for some well-known algorithms, including algorithms of…

Computational Complexity · Computer Science 2015-08-06 V. P. Burichenko