Evaluation and FPGA Implementation of Sparse Linear Solvers for Video Processing Applications

Abstract

Sparse linear systems are commonly used in video processing applications, such as edge-aware filtering or video retargeting. Due to the 2-D nature of images, the involved problem sizes are large and thus solving such systems is computationally challenging. In this paper, we address sparse linear solvers for real-time video applications. We investigate several solver techniques, discuss hardware trade-offs, and provide field-programmable gate array (FPGA) architectures and implementation results of a Cholesky direct solver and of an iterative BiCGSTAB solver. The FPGA implementations solve 32 k × 32 k matrices at up to 50 f/s and outperform software implementations by at least one order of magnitude.