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A 4-year $2.6 million grant from the National Institute of Biomedical Imaging and Bioengineering (NIBIB), to perform real-time CT imaging dose calculations (2012 2016)
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Participants:RPI - Xu, Ji, Carothers, and ShephardMass General Hospital Kalra and Liu GE Global Research FitzGerald LANL - Brown
IntroductionMonte Carlo radiation computing is the gold standard, but time-consumingTraditional parallel schemes use CPUsMultiprocessingmultithreadingHardware accelerators are emergingGPUCoprocessor
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Exa-scale HPC depends on hardware accelerators(Among Top 10 supercomputer as of June 17, 2013)
rankNameRmaxRpeakConfig1Tianhe-233.9 PF54.9 PF32,000 Intel Xeon E5-2692 (12-core)48,000 Intel Xeon Phi coprocessor 31S1P2Titan17.6 PF27.1 PF18,688 AMD Opteron 6274 (16-core)18,688 NVIDIA K20x GPU
3GPU offers: - Massive data-parallel computing power- Cost and energy efficiency- Flexible programming architecture (CUDA)
Stream Processors
Single Instruction, Multiple Threads (SIMT)
Challenges: obtain efficiency and high performance
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Preliminary Clinical ResultsCT images converted to voxelized phantom
Patient CT imaging dose calculated by ARCHER- 1 GPU: 7.7 seconds- 6 GPUs: 1.4 seconds real-time speed 5
10 layers added together5DEMO ARCHER in 4s and GPU (12 HT) in 40s6
Long-term Vision: ARCHER - A Testbed(Accelerated Radiation-transport Computations in Heterogeneous EnviRonments)
www.archer-mc.com7