Optimization principles and application performance evaluation of a multithreaded GPU using CUDA
Proceedings of the 13th ACM SIGPLAN Symposium on Principles and practice of parallel programming
GPU acceleration of cutoff pair potentials for molecular modeling applications
Proceedings of the 5th conference on Computing frontiers
Accelerating advanced MRI reconstructions on GPUs
Journal of Parallel and Distributed Computing
IEEE Transactions on Signal Processing
Deterministic edge-preserving regularization in computed imaging
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Accelerating iterative field-compensated MR image reconstruction on GPUS
ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
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With the explosive development of advanced image reconstruction algorithms, there is an urgent need for acceleration of these algorithms to facilitate their use in practical applications. This paper describes our experience using graphics processing units (GPUs) for advanced MR image reconstruction from non-Cartesian data. We show that implementation of MR image reconstruction on NVIDIA CUDA-enabled GPUs can significantly accelerate the solution of this type of image reconstruction problem. Given the acceleration afforded by the GPU, we expect our strategy to be applied to other computationally intensive imaging algorithms.