How to multiply matrices faster
How to multiply matrices faster
Synthesis of an Optimal Family of Matrix Multiplication Algorithms on Linear Arrays
IEEE Transactions on Computers
A Study of Pipelining in Computing Arrays
IEEE Transactions on Computers
The optimality of Winograd's formula
Communications of the ACM
Automatic synthesis of systolic arrays from uniform recurrent equations
ISCA '84 Proceedings of the 11th annual international symposium on Computer architecture
Techniques for the design of parallel and pipelined vlsi systems for numerical computation with special reference to signal processing applications (systolic array, scheduling)
Data Flow Representation of Iterative Algorithms for Systolic Arrays
IEEE Transactions on Computers
Design of Efficient Regular Arrays for Matrix Multiplication by Two-Step Regularization
IEEE Transactions on Parallel and Distributed Systems
Some New Designs of 2-D Array for Matrix Multiplication and Transitive Closure
IEEE Transactions on Parallel and Distributed Systems
A Fast Algorithm for Matrix Multiplication and Its Efficient Realization on Systolic Arrays
Cybernetics and Systems Analysis
Massive parallel processing for matrix multiplication: a systolic approach
Highly parallel computaions
Hexagonal systolic arrays for matrix multiplication
Highly parallel computaions
| Hi-index | 14.98 |
The authors present a regular iterative algorithm for matrix multiplication and show that several well-known matrix multiplication arrays are directly obtained from it, differing only in the choice of iteration vector. They then present a regular iterative algorithm for matrix multiplication using the S. Winograd method (1968) and show in detail how to derive one array from this algorithmic description. Other arrays in the same family can similarly be obtained for different choices of the iteration space. The new arrays compute the product of two matrices faster than available conventional arrays and use a smaller number of processor cells.