2015
DOI: 10.1016/j.anucene.2014.08.062
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ARCHER, a new Monte Carlo software tool for emerging heterogeneous computing environments

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Cited by 23 publications
(19 citation statements)
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“…A GPU-accelerated Monte Carlo code, ARCHER, previously developed by members of this group was used in this study to calculate organ doses 20,21,43 . ARCHER is used in this study to simulate the transport of low-energy X-ray photons in heterogeneous media defined by the patient CT images where photoelectric effect, Compton scattering, and Rayleigh scattering can take place.…”
Section: B Organ Dose Calculationsmentioning
confidence: 99%
“…A GPU-accelerated Monte Carlo code, ARCHER, previously developed by members of this group was used in this study to calculate organ doses 20,21,43 . ARCHER is used in this study to simulate the transport of low-energy X-ray photons in heterogeneous media defined by the patient CT images where photoelectric effect, Compton scattering, and Rayleigh scattering can take place.…”
Section: B Organ Dose Calculationsmentioning
confidence: 99%
“…22,23 Monte Carlo simulations are traditionally slow, though recent advancements in acceleration and GPU implementation have greatly reduced run times. [24][25][26][27] Rapid estimation of the deposited dose distribution may enable patient-specific CT dosimetry, which could facilitate more accurate dose reporting and patient-specific CT protocol optimization.…”
Section: Introductionmentioning
confidence: 99%
“…Comparative studies should also consider software related labor expenses. When we recently compared the performances of ARCHER-an MC dosimetry code developed from scratch by my Ph.D. students [11][12][13] -in the CPU, GPU, and MIC platforms, we found that GPU's advantages as a dose engine are less dramatic than some of those reported in the literature. All things considered, traditional CPU clusters and MIC remain serious competitors to GPUs when energy efficiency is not the priority.…”
Section: Rebuttal: Xun Jia Phdmentioning
confidence: 54%
“…Intel's Xeon Phi coprocessor, for example, which comes with 60 embedded Pentium cores, is capable of achieving a similar level of parallelism as GPUs. [11][12][13] Adopting the coprocessor is relatively easy and a large number of them are, in fact, used in Tianhe-2-the world's number-1 supercomputer. The "heterogeneous computing" era has just begun and it is uncertain which hardware (and software) technology will dominate the market.…”
Section: Opening Statementmentioning
confidence: 99%