Accelerate Compression Sensing Reconstruction Algorithms Using GPU

The signal reconstruction in compressive sensing (CS) requires a large amount of data processing. However the traditional CPU has no advantage on vector calculation. To deal with this issue, we design a parallel computing architecture using CUDA. Based on GPU-CPU parallel programming technology, and we realize three fast and efficient CS image reconstruction algorithms, including OMP, TwIST, and linear Bregman algorithm.