Comparison of Two Accelerators for Monte Carlo Radiation Transport Calculations, NVIDIA Tesla M2090 GPU and Intel Xeon Phi 5110p Coprocessor: A Case Study for X-ray CT Imaging Dose Calculation
1 Nuclear Engineering Program, Rensselaer Polytechnic Institute, Troy, New York 12180, USA
2 Computer Science Department, Rensselaer Polytechnic Institute
* Corresponding Author: email@example.com
Hardware accelerators are currently becoming increasingly important in boosting high performance computing sys- tems. In this study, we tested the performance of two accelerator models, NVIDIA Tesla M2090 GPU and Intel Xeon Phi 5110p coprocessor, using a new Monte Carlo photon transport package called ARCHER-CT we have developed for fast CT imaging dose calculation. The package contains three code variants, ARCHER − CTCPU, ARCHER – CTGPU and ARCHER − CTCOP to run in parallel on the multi-core CPU, GPU and coprocessor architectures respectively. A detailed GE LightSpeed Multi-Detector Computed Tomography (MDCT) scanner model and a family of voxel patient phantoms were included in the code to calculate absorbed dose to radiosensitive organs under specified scan protocols. The results from ARCHER agreed well with those from the production code Monte Carlo N-Particle eXtended (MCNPX). It was found that all the code variants were significantly faster than the parallel MCNPX running on 12 MPI processes, and that the GPU and coprocessor performed equally well, being 2.89~4.49 and 3.01~3.23 times faster than the parallel ARCHER − CTCPU running with 12 hyperthreads.
Key words: Monte Carlo / NVIDIA GPU / Fermi / Intel Xeon Phi coprocessor / MIC / CT imaging dose
© Owned by the authors, published by EDP Sciences, 2014