A new general purpose systolic array for matrix computations
Hai P. Le · 2000
In this thesis, we propose a new systolic architecture which is based on the Faddeev's algorithm. Because Faddeev's algorithm is inherently general purpose, our architecture is able to perform a wide class of matrix computations. And since the architecture is systolic based, it brings massive parallelism to all of its computations. As a result, many matrix operations including addition, multiplication, inversion, LU-decomposition, transpose, and solutions to linear systems of equations can now be performed extremely fast. In addition, our design introduces several concepts which are new to systolic architectures: - It can be re-configured during run time to perform different functions with the uses of various control signals propagating throughout the arrays. - It allows for maximum overlaps of processing between consecutive computations, thereby increasing system throughput.