Parallel Reconstruction for Parallel Imaging SPACERIP on Cellular Computer Architecture

Recently the new field of parallel imaging accusation has the potential to revolutionize the field of fast MR imaging. The SPACE RIP technique is one of the parallel imaging methods which uses multiple receiver coil and utilizes the sensitivity profile information from a number of receiver coils in order to reduce the acquisition time. The image reconstruction problem of SPACE RIP is a computation intensive task, which need to be parallelized to further reduce the reconstruction time. In this paper, we analyzed the algorithm and identified the program bottleneck to be parallelized. The loop level parallelization is implemented with Pthread, OpenMP and MPI. Furthermore, since the reconstruction uses Singular Value decomposition (SVD) to solve the matrix pseudoinverse, we implemented the one sided Jacobi parallel SVD on the state-of-art cellular computer architecture Cyclops64 to speedup the problem at the fine grain level. Experimental result shows that cellular computer architecture has very small overhead and thus suitable for fine grain level parallelization.