Eigen values and vectors computations on VIRTEX-5 FPGA platform cyclic Jacobi's algorithm using systolic array architecture
Gopinath Mahale, Prashant Bartakke · 2011
The parallel iterative algorithms are the major advancements in the field of computing. These algorithms lead to efficient usage of hardware as well as obtaining faster results. In this paper, we describe architecture to compute eigen values and eigen vectors of a matrix having dimensions up to 50 × 50 using cyclic Jacobi's Algorithm. Systolic array architecture is used to apply it to matrices of larger dimensions. We have implemented the architecture on FPGA Vertex-5 that takes about 8059 LUT slices out of 69120 slices for matrices of dimensions 50 × 50.