Journal
JOURNAL OF IMAGING
Volume 4, Issue 3, Pages -Publisher
MDPI
DOI: 10.3390/jimaging4030051
Keywords
heterogeneous systemarchitecture (HSA); graphic processing unit (GPU); multi-core system; magnetic resonance imaging (MRI); total variation (TV)
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Funding
- Ministry of Science and Technology, Taiwan
- Cambridge Commonwealth, European and International Trust, Cambridge, UK
- Ministry of Education, Taiwan
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A Python non-uniform fast Fourier transform (PyNUFFT) package has been developed to accelerate multidimensional non-Cartesian image reconstruction on heterogeneous platforms. Since scientific computing with Python encompasses a mature and integrated environment, the time efficiency of the NUFFT algorithm has been a major obstacle to real-time non-Cartesian image reconstruction with Python. The current PyNUFFT software enables multi-dimensional NUFFT accelerated on a heterogeneous platform, which yields an efficient solution to many non-Cartesian imaging problems. The PyNUFFT also provides several solvers, including the conjugate gradient method, '1 total variation regularized ordinary least square (L1TV-OLS), and '1 total variation regularized least absolute deviation (L1TV-LAD). Metaprogramming libraries have been employed to accelerate PyNUFFT. The PyNUFFT package has been tested on multi-core central processing units (CPUs) and graphic processing units (GPUs), with acceleration factors of 6.3-9.5x on a 32-thread CPU platform and 5.4-13x on a GPU.
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