A 4-year $2.6 million grant from the National Institute of Biomedical Imaging and Bioengineering...
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- Slide 1
- 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) 1 Participants: RPI - Xu,
Ji, Carothers, and Shephard Mass General Hospital Kalra and Liu GE
Global Research FitzGerald LANL - Brown
- Slide 2
- Introduction Monte Carlo radiation computing is the gold
standard, but time-consuming Traditional parallel schemes use CPUs
Multiprocessing multithreading Hardware accelerators are emerging
GPU Coprocessor 2
- Slide 3
- Exa-scale HPC depends on hardware accelerators (Among Top 10
supercomputer as of June 17, 2013) rankName RmaxRpeak Config 1
Tianhe-2 33.9 PF54.9 PF 32,000 Intel Xeon E5-2692 (12-core) 48,000
Intel Xeon Phi coprocessor 31S1P 2 Titan 17.6 PF27.1 PF 18,688 AMD
Opteron 6274 (16-core) 18,688 NVIDIA K20x GPU
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- GPU offers: - Massive data-parallel computing power - Cost and
energy efficiency - Flexible programming architecture (CUDA) Stream
Processors Single Instruction, Multiple Threads (SIMT)
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- Preliminary Clinical Results CT 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
- Slide 6
- DEMO ARCHER in 4s and GPU (12 HT) in 40s 6
- Slide 7
- Long-term Vision: ARCHER - A Testbed (Accelerated
Radiation-transport Computations in Heterogeneous EnviRonments)
www.archer-mc.com