Abstract: We consider computing the QR factorization with column pivoting (QRCP) for a tall and skinny matrix, which has important applications including low-rank approximation and rank determination.

with being the (tall thin) matrix from the ML-cup dataset by Prof. Micheli, , and is a random vector. (A1) is thin QR factorization via Householder reflectors, cf. also Lecture 10. (A2) is a variant ...

We implement fixed-point matrix inversion on a Virtex-4 FPGA using a synthesizable QR-decomposition MATLAB model and the AccelDSP Synthesis tool. The resulting function occupies 12% of a XC4VSX55 ...