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Related papers: Designing Strassen's algorithm

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The multiplication of a matrix by its transpose, $A^T A$, appears as an intermediate operation in the solution of a wide set of problems. In this paper, we propose a new cache-oblivious algorithm (ATA) for computing this product, based upon…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-10-08 Viviana Arrigoni , Filippo Maggioli , Annalisa Massini , Emanuele Rodolà

After Strassen presented the first sub-cubic matrix multiplication algorithm, many Strassen-like algorithms are presented. Most of them with low asymptotic cost have large hidden leading coefficient which are thus impractical. To reduce the…

Symbolic Computation · Computer Science 2022-03-31 Pu Wu , Huiqing Jiang , Zehui Shao , Jin Xu

Matrix multiplication $A^t A$ appears as intermediate operation during the solution of a wide set of problems. In this paper, we propose a new cache-oblivious algorithm for the $A^t A$ multiplication. Our algorithm, A$\scriptstyle…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-02-07 Viviana Arrigoni , Annalisa Massini

For almost 35 years, Sch{\"o}nhage-Strassen's algorithm has been the fastest algorithm known for multiplying integers, with a time complexity O(n $\times$ log n $\times$ log log n) for multiplying n-bit inputs. In 2007, F{\"u}rer proved…

Symbolic Computation · Computer Science 2018-04-18 Svyatoslav Covanov , Emmanuel Thomé

Parallel matrix multiplication is one of the most studied fundamental problems in distributed and high performance computing. We obtain a new parallel algorithm that is based on Strassen's fast matrix multiplication and minimizes…

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

We further develop the group-theoretic approach to fast matrix multiplication introduced by Cohn and Umans, and for the first time use it to derive algorithms asymptotically faster than the standard algorithm. We describe several families…

Group Theory · Mathematics 2012-03-15 Henry Cohn , Robert Kleinberg , Balazs Szegedy , Christopher Umans

It is widely known that the lower bound for the algorithmic complexity of square matrix multiplication resorts to at least $n^2$ arithmetic operations. The justification builds upon the following reasoning: given that there are $2 n^2$…

Data Structures and Algorithms · Computer Science 2023-11-13 Hugo Daniel Macedo

Matrix multiplication is a fundamental computation in many scientific disciplines. In this paper, we show that novel fast matrix multiplication algorithms can significantly outperform vendor implementations of the classical algorithm and…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-01-08 Austin R. Benson , Grey Ballard

In 1977, Strassen invented a famous baby-step/giant-step algorithm that computes the factorial $N!$ in arithmetic complexity quasi-linear in $\sqrt{N}$. In 1988, the Chudnovsky brothers generalized Strassen's algorithm to the computation of…

Symbolic Computation · Computer Science 2020-12-17 Alin Bostan , Sergey Yurkevich

The Strassen algorithm and Winograd's variant accelerate matrix multiplication by using fewer arithmetic operations than standard matrix multiplication. Although many papers have been published to accelerate single- as well as…

Numerical Analysis · Mathematics 2015-10-27 Tomonori Kouya

Obeying constraints imposed by classical physics, we give optimal fine-grained algorithms for matrix multiplication and problems involving graphs and mazes, where all calculations are done in 3-dimensional space. We assume that whatever the…

Data Structures and Algorithms · Computer Science 2024-12-20 Quentin F. Stout

This paper presents a new fast, highly scalable distributed matrix multiplication algorithm on Apache Spark, called Stark, based on Strassen's matrix multiplication algorithm. Stark preserves Strassen's 7 multiplications scheme in a…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-11-26 Chandan Misra , Sourangshu Bhattacharya , Soumya K. Ghosh

Fast algorithms for matrix multiplication, namely those that perform asymptotically fewer scalar operations than the classical algorithm, have been considered primarily of theoretical interest. Apart from Strassen's original algorithm, few…

Numerical Analysis · Computer Science 2016-07-26 Grey Ballard , Austin R. Benson , Alex Druinsky , Benjamin Lipshitz , Oded Schwartz

In 1977, Strassen presented a deterministic and rigorous algorithm for solving the problem of computing the prime factorization of natural numbers $N$. His method is based on fast polynomial arithmetic techniques and runs in time…

Number Theory · Mathematics 2019-10-22 Markus Hittmeir

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

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. In this paper we show that \alpha>0.30298, which improves the previous…

Data Structures and Algorithms · Computer Science 2021-10-05 François Le Gall

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

We propose a more accurate variant of an algorithm for multiplying 4x4 matrices using 48 multiplications over any ring containing an inverse of 2. This algorithm has an error bound exponent of only log 4 $\gamma$$\infty$,2 $\approx$ 2.386.…

Data Structures and Algorithms · Computer Science 2026-03-20 Jean-Guillaume Dumas , Clément Pernet , Alexandre Sedoglavic

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

We study neural networks whose only non-linear components are multipliers, to test a new training rule in a context where the precise representation of data is paramount. These networks are challenged to discover the rules of matrix…

Numerical Analysis · Mathematics 2016-01-28 Veit Elser