Matrix multiplication is a binary operation that produces a matrix from two matrices, where the number of columns in the first matrix must be equal to the number of rows in the second. It was first described by Jacques Philippe Marie Binet in 1812 and has numerous applications in mathematics, physics, economics, and engineering. Computing matrix products is a central operation in all computational applications of linear algebra.

UC Berkeley

Spring 2020

The course addresses programming parallel computers to solve complex scientific and engineering problems. It covers an array of parallelization strategies for numerical simulation, data analysis, and machine learning, and provides experience with popular parallel programming tools.

No concepts data

+ 36 more conceptsStanford University

Fall 2022

Focused on principles and trade-offs in designing modern parallel computing systems, this course also teaches parallel programming techniques. It is intended for students looking to understand both parallel hardware and software design. Prerequisite knowledge in computer systems is required.

No concepts data

+ 45 more conceptsUC Berkeley

Spring 2020

This is an introductory course to computer science theory, exploring the design and analysis of various algorithms, number theory, and complexity. The prerequisites include familiarity with mathematical induction, big-O notation, basic data structures, and programming in a standard language.

No concepts data

+ 36 more concepts