Novel parallel Givens QR decomposition implementation on VLIW architecture with Efficient memory access for real time image processing applications

Abstract

Compressed Sensing (CS) methods impact is important in the health care systems. The acquisition and the processing speed of many medical imaging applications is highly improved using this technique. Orthogonal Matching Pursuit (OMP) is one of the widely used image reconstruction algorithms in CS techniques. Traditionally, OMP is divided on two main tasks: optimization stage and least square problem (LSP) resolution stage. The LSP resolution is the most complex and time consuming step in OMP. QRD is one of the main techniques used to solve the LSP in a very short time. However, the increasing image and video resolutions (UHDTV) makes the real time constraints very tight. In this paper, a novel implementation of QRD on VLIW DSP architecture with an efficient memory access approach is introduced. An instruction, data and loop levels parallelism (ILP, DLP and LLP) based Givens QRD kernel is designed. A robust memory access management based on intelligent loading/storing strategies and proficient data alignment techniques is adopted for the proposed parallel implementation. Therefore, memory read misses and CPU stalls are significantly diminished. As a final result the processing time is greatly reduced. The proposed scheme is implemented on C6678 DSP and reaches 2.22 GFLOPS. The performances achieved are 7.4, 3.83 and 2 times faster than standard Givens, Texas Instrument optimized QRD and state of the art, respectively.