Systolic-type implementation of matrix computations based on the Faddeev algorithm

Deals with the problem of enhancing the versatility of VLSI processor arrays without undue addition of hardware, time/control overhead, and software complexity. A promising approach to this problem is based on matrix computations carried out through the Faddeev algorithm. We design a fixed-size, linear array architecture with fully local communications and straightforward control requirements. This high-throughput, systolic-type architecture allows us to minimize both I/O requirements and the number of processing elements performing complicated operations like divisions. To derive the array from a formal description of the Faddeev algorithm based on Gaussian elimination with partial pivoting, we use purposive transformations of the basic dependence graph of the algorithm before its space-time mappings onto array architectures