GMRES: a generalized minimal residual algorithm for solving nonsymmetric linear systems
SIAM Journal on Scientific and Statistical Computing
Iterative Methods for Sparse Linear Systems
Iterative Methods for Sparse Linear Systems
Cg: a system for programming graphics hardware in a C-like language
ACM SIGGRAPH 2003 Papers
Sparse matrix solvers on the GPU: conjugate gradients and multigrid
ACM SIGGRAPH 2003 Papers
OpenGL(R) Shading Language
Brook for GPUs: stream computing on graphics hardware
ACM SIGGRAPH 2004 Papers
LU-GPU: Efficient Algorithms for Solving Dense Linear Systems on Graphics Hardware
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
GMRES Method on Lightweight GRID System
ISPDC '05 Proceedings of the The 4th International Symposium on Parallel and Distributed Computing
Proceedings of the 44th annual Design Automation Conference
Scan primitives for GPU computing
Proceedings of the 22nd ACM SIGGRAPH/EUROGRAPHICS symposium on Graphics hardware
Efficient gather and scatter operations on graphics processors
Proceedings of the 2007 ACM/IEEE conference on Supercomputing
GPU acceleration of cutoff pair potentials for molecular modeling applications
Proceedings of the 5th conference on Computing frontiers
Relational joins on graphics processors
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Sparse matrix computations on manycore GPU's
Proceedings of the 45th annual Design Automation Conference
Scalable parallel programming with CUDA
ACM SIGGRAPH 2008 classes
Parallel GMRES implementation for solving sparse linear systems on GPU clusters
Proceedings of the 19th High Performance Computing Symposia
GPU accelerated CAE using open solvers and the cloud
ACM SIGARCH Computer Architecture News
Sparse systems solving on GPUs with GMRES
The Journal of Supercomputing
Parallel sparse linear solver GMRES for GPU clusters with compression of exchanged data
Euro-Par'11 Proceedings of the 2011 international conference on Parallel Processing
New basic linear algebra methods for simulation on GPUs
Proceedings of the 2011 Grand Challenges on Modeling and Simulation Conference
GPU-accelerated preconditioned iterative linear solvers
The Journal of Supercomputing
CUDA acceleration of a matrix-free Rosenbrock-K method applied to the shallow water equations
ScalA '13 Proceedings of the Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems
A novel finite element method assembler for co-processors and accelerators
IA^3 '13 Proceedings of the 3rd Workshop on Irregular Applications: Architectures and Algorithms
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Current many-core GPUs have enormous processing power, and unlocking this power for general-purpose computing is very attractive due to their low cost and efficient power utilization. However, the fine-grained parallelism and the stream-programming model supported by these GPUs require a paradigm shift, especially for algorithm designers. In this paper we present the design of a GPU-based sparse linear solver using the Generalized Minimum RESidual (GMRES) algorithm in the CUDA programming environment. Our implementation achieved a speedup of over 20x on the Tesla T10P based GTX280 GPU card for benchmarks with from a few thousands to a few millions unknowns.