2005ACM Transactions on AlgorithmsRequires access

Fast sparse matrix multiplication

Raphael Yuster, Uri Zwick

Open publisher page 259 citations

Abstract

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 B using O ( m 0.7 n 1.2 + n 2+ o (1) ) algebraic operations (i.e., multiplications, additions and subtractions) over R . The naïve matrix multiplication algorithm, on the other hand, may need to perform Ω( mn ) operations to accomplish the same task. For m ≤ n 1.14 , the new algorithm performs an almost optimal number of only n 2+ o (1) operations. For m ≤ n 1.68 , the new algorithm is also faster than the best known matrix multiplication algorithm for dense matrices which uses O ( n 2.38 ) algebraic operations. The new algorithm is obtained using a surprisingly straightforward combination of a simple combinatorial idea and existing fast rectangular matrix multiplication algorithms. We also obtain improved algorithms for the multiplication of more than two sparse matrices. As the known fast rectangular matrix multiplication algorithms are far from being practical, our result, at least for now, is only of theoretical value.

About this research paper

What this paper is about

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 B using O ( m 0.7 n 1.2 + n 2+ o (1) ) algebraic operations (i.e., multiplications, additions and subtractions) over R . The naïve matrix multiplication algorithm, on the other hand, may need to perform Ω( mn ) operations to accomplish the same task. For m ≤ n 1.14 , the new algorithm performs an almost optimal number of only n 2+ o (1) operations. For m ≤ n 1.68 , the new algorithm is also faster than the best known matrix multiplication algorithm for dense matrices which uses O ( n 2.38 ) algebraic operations. The new algorithm is obtained using a surprisingly straightforward combination of a simple combinatorial idea and existing fast rectangular matrix multiplication algorithms. We also obtain improved algorithms for the multiplication of more than two sparse matrices. As the known fast rectangular matrix multiplication algorithms are far from being practical, our result, at least for now, is only of theoretical value.

Why it matters

OpenAlex reports 259 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

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 B using O ( m 0.7 n 1.2 + n 2+ o (1) ) algebraic operations (i.e., multiplications, additions and subtractions) over R . The naïve matrix multiplication algorithm, on the other hand, may need to perform Ω( mn ) operations to accomplish the same task. For m ≤ n 1.14 , the new algorithm performs an almost optimal number of only n 2+ o (1) operations. For m ≤ n 1.68 , the new algorithm is also faster than the best known matrix multiplication algorithm for dense matrices which uses O ( n 2.38 ) algebraic operations. The new algorithm is obtained using a surprisingly straightforward combination of a simple combinatorial idea and existing fast rectangular matrix multiplication algorithms. We also obtain improved algorithms for the multiplication of more than two sparse matrices. As the known fast rectangular matrix multiplication algorithms are far from being practical, our result, at least for now, is only of theoretical value.

Key concepts: Matrix multiplication, Multiplication algorithm, Multiplication (music), Strassen algorithm, Matrix (chemical analysis), Mathematics, Freivalds' algorithm, Algebraic number

Related papers

Back to paper searchBrowse research topicsOriginal source
Fast sparse matrix multiplication — Research Paper | ScholarLens