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Fano Cavity Test of Proton Transport in Monte Carlo Codes Running On GPU and Xeon Phi

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E Sterpin

E Sterpin1*, J Sorriaux1 , J Schuemann2 , K Souris1 , J Lee1 , S Vynckier1 , X Jia3 , S Jiang3 , H Paganetti2 , (1) Universite catholique de Louvain, Brussels, Brussels, (2) Massachusetts General Hospital, Boston, MA, (3) The University of Texas Southwestern Medical Ctr, Dallas, TX,

Presentations

SU-E-T-180 Sunday 3:00PM - 6:00PM Room: Exhibit Hall

Purpose: In proton dose calculation, clinically compatible speeds are now achieved with Monte Carlo codes (MC) that combine 1) adequate simplifications in the physics of transport and 2) the use of hardware architectures enabling massive parallel computing (like GPUs). However, the uncertainties related to the transport algorithms used in these codes must be kept minimal. Such algorithms can be checked with the so-called "Fano cavity test". We implemented the test in two codes that run on specific hardware: gPMC on an nVidia GPU and MCsquare on an Intel Xeon Phi (60 cores).

Methods: gPMC and MCsquare are designed for transporting protons in CT geometries. Both codes use the method of fictitious interaction to sample the step-length for each transport step. The considered geometry is a water cavity (2x2x0.2 cm³, 0.001 g/cm³) in a 10x10x50 cm³ water phantom (1 g/cm³). CPE in the cavity is established by generating protons over the phantom volume with a uniform momentum (energy E) and a uniform intensity per unit mass I. Assuming no nuclear reactions and no generation of other secondaries, the computed cavity dose should equal IE, according to Fano's theorem. Both codes were tested for initial proton energies of 50, 100, and 200 MeV.

Results: For all energies, gPMC and MCsquare are within 0.3 and 0.2 % of the theoretical value IE, respectively (0.1% standard deviation). Single-precision computations (instead of double) increased the error by about 0.1% in MCsquare.

Conclusion: Despite the simplifications in the physics of transport, both gPMC and MCsquare successfully pass the Fano test. This ensures optimal accuracy of the codes for clinical applications within the uncertainties on the underlying physical models. It also opens the path to other applications of these codes, like the simulation of ion chamber response.

Funding Support, Disclosures, and Conflict of Interest: J. Sorriaux and K. Souris are financially supported by a public-private partnership involving the company Ion Beam Applications (IBA).


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