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The Tensor Isomorphism problem (TI) has recently emerged as having connections to multiple areas of research within complexity and beyond, but the current best upper bound is essentially the brute force algorithm. Being an algebraic…

Computational Complexity · Computer Science 2023-06-01 Nicola Galesi , Joshua A. Grochow , Toniann Pitassi , Adrian She

Multiplication is an essential step in a lot of calculations. In this paper we look at multiplication of 2 binary polynomials of degree at most $n-1$, modulo an irreducible polynomial of degree $n$ with $2n$ input and $n$ output qubits,…

Quantum Physics · Physics 2020-02-27 Iggy van Hoof

We introduce a variant of PCPs, that we refer to as rectangular PCPs, wherein proofs are thought of as square matrices, and the random coins used by the verifier can be partitioned into two disjoint sets, one determining the row of each…

Computational Complexity · Computer Science 2022-11-24 Amey Bhangale , Prahladh Harsha , Orr Paradise , Avishay Tal

We consider the time and space required for quantum computers to solve a wide variety of problems involving matrices, many of which have only been analyzed classically in prior work. Our main results show that for a range of linear algebra…

Computational Complexity · Computer Science 2025-11-03 Paul Beame , Niels Kornerup , Michael Whitmeyer

Sparse matrix multiplication is an important component of linear algebra computations. Implementing sparse matrix multiplication on an associative processor (AP) enables high level of parallelism, where a row of one matrix is multiplied in…

Mathematical Software · Computer Science 2017-05-23 L. Yavits , A. Morad , R. Ginosar

We describe an algorithm for fast multiplication of skew polynomials. It is based on fast modular multiplication of such skew polynomials, for which we give an algorithm relying on evaluation and interpolation on normal bases. Our…

Symbolic Computation · Computer Science 2017-02-07 Xavier Caruso , Jérémy Le Borgne

We analyze the bit complexity of efficient algorithms for fundamental optimization problems, such as linear regression, $p$-norm regression, and linear programming (LP). State-of-the-art algorithms are iterative, and in terms of the number…

Data Structures and Algorithms · Computer Science 2023-04-06 Mehrdad Ghadiri , Richard Peng , Santosh S. Vempala

We consider the problem of massive matrix multiplication, which underlies many data analytic applications, in a large-scale distributed system comprising a group of worker nodes. We target the stragglers' delay performance bottleneck, which…

Information Theory · Computer Science 2020-04-10 Qian Yu , Mohammad Ali Maddah-Ali , A. Salman Avestimehr

The $N$th power of a polynomial matrix of fixed size and degree can be computed by binary powering as fast as multiplying two polynomials of linear degree in~$N$. When Fast Fourier Transform (FFT) is available, the resulting complexity is…

Symbolic Computation · Computer Science 2023-05-29 Alin Bostan , Vincent Neiger , Sergey Yurkevich

Fast matrix multiplication algorithms are asymptotically faster than the classical cubic-time algorithm, but they are often slower in practice. One important obstacle is the use of complex coefficients, which increases arithmetic overhead…

Rings and Algebras · Mathematics 2026-02-16 Yoav Moran , Oded Schwartz , Shuncheng Yuan

Distributed matrix computations -- matrix-matrix or matrix-vector multiplications -- are well-recognized to suffer from the problem of stragglers (slow or failed worker nodes). Much of prior work in this area is (i) either sub-optimal in…

Information Theory · Computer Science 2020-06-03 Anindya B. Das , Aditya Ramamoorthy , Namrata Vaswani

We study matrix multiplication in the low-bandwidth model: There are $n$ computers, and we need to compute the product of two $n \times n$ matrices. Initially computer $i$ knows row $i$ of each input matrix. In one communication round each…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-06-02 Chetan Gupta , Juho Hirvonen , Janne H. Korhonen , Jan Studený , Jukka Suomela

Matrix multiplication (hereafter we use the acronym MM) is among the most fundamental operations of modern computations. The efficiency of its performance depends on various factors, in particular vectorization, data movement and arithmetic…

Data Structures and Algorithms · Computer Science 2015-02-09 Victor Y. Pan

Fault tolerance is a major concern in distributed computational settings. In the classic master-worker setting, a server (the master) needs to perform some heavy computation which it may distribute to $m$ other machines (workers) in order…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-10-30 Keren Censor-Hillel , Yuka Machino , Pedro Soto

We propose efficient parallel algorithms and implementations on shared memory architectures of LU factorization over a finite field. Compared to the corresponding numerical routines, we have identified three main difficulties specific to…

Symbolic Computation · Computer Science 2014-02-17 Jean-Guillaume Dumas , Thierry Gautier , Clément Pernet , Ziad Sultan

In this paper, the canonical polyadic (CP) decomposition of tensors that corresponds to matrix multiplications is studied. Finding the rank of these tensors and computing the decompositions is a fundamental problem of algebraic complexity…

Computational Complexity · Computer Science 2021-04-13 Petr Tichavsky

In this work faster unsigned multiplication has been achieved by using a combination of High Performance Multiplication [HPM] column reduction technique and implementing a N-bit multiplier using 4 N/2-bit multipliers (recursive…

Hardware Architecture · Computer Science 2011-10-20 V. Sreedeep , B. Ramkumar , Harish M Kittur

The fastest known algorithm for factoring a degree $n$ univariate polynomial over a finite field $\mathbb{F}_q$ runs in time $O(n^{3/2 + o(1)}\text{polylog } q)$, and there is a reason to believe that the $3/2$ exponent represents a…

Data Structures and Algorithms · Computer Science 2025-11-17 Chris Umans , Siki Wang

We show that the product of an nx3 matrix and a 3x3 matrix over a commutative ring can be computed using 6n+3 multiplications. For two 3x3 matrices this gives us an algorithm using 21 multiplications. This is an improvement with respect to…

Computational Complexity · Computer Science 2020-07-28 Andreas Rosowski

The All-Pairs Shortest Paths (APSP) is a foundational problem in theoretical computer science. Approximating APSP in undirected unweighted graphs has been studied for many years, beginning with the work of Dor, Halperin and Zwick…

Data Structures and Algorithms · Computer Science 2025-11-10 Ce Jin , Yael Kirkpatrick , Michał Stawarz , Virginia Vassilevska Williams