Kathryn Fontaine
ABSTRACT
Yale MOLAR is an in-house Positron Emission Tomography (PET) image reconstruction application written in C++ and MPI. It deals with hundreds of millions of lines-of-response (LORs) independently to reconstruct an image. The nature of the image reconstruction process makes MOLAR an ideal candidate for GPU acceleration. In this study, we present our work on accelerating MOLAR with CUDA, and show the results that demonstrate the effectiveness and correctness of our CUDA implementation. Overall, Yale MOLAR with CUDA runs up to 6 times faster than the CPU-only code, reducing a typical high resolution image reconstruction time from several hours to less than one hour.
- W. Craig Barker, Shanthalaxmi Thada, and William Dieckmann. 2009. A GPU-accelerated implementation of the MOLAR PET reconstruction package. In 2009 IEEE Nuclear Science Symposium Conference Record (NSS/MIC). 4114–4119. https://doi.org/10.1109/NSSMIC.2009.5402353Google Scholar
Cross Ref
- C.A. Johnson, S. Thada, M. Rodriguez, Y. Zhao, A.R. Iano-Fletcher, J.-S. Liow, W.C. Barker, R.L. Martino, and R.E. Carson. 2004. Software architecture of the MOLAR-HRRT reconstruction engine. In IEEE Symposium Conference Record Nuclear Science 2004., Vol. 6. 3956–3960. https://doi.org/10.1109/NSSMIC.2004.1466744Google ScholarCross Ref
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