A Fast GPU Implementation for Solving Sparse Ill-Posed Linear Equation Systems [chapter]

Florian Stock, Andreas Koch
2010 Lecture Notes in Computer Science  
Image reconstruction, a very compute-intense process in general, can often be reduced to large linear equation systems represented as sparse under-determined matrices. Solvers for these equation systems (not restricted to image reconstruction) spend most of their time in sparse matrix-vector multiplications (SpMV). In this paper we will present a GPU-accelerated scheme for a Conjugate Gradient (CG) solver, with focus on the SpMV. We will discuss and quantify the optimizations employed to
more » ... a soft-real time constraint as well as alternative solutions relying on FPGAs, the Cell Broadband Engine, a highly optimized SSE-based software implementation, and other GPU SpMV implementations.
doi:10.1007/978-3-642-14390-8_48 fatcat:4ybhuquhhre43gshr5tvpub7iq