Highlights
- •Field programmable gate arrays (FPGAs) can linearly speed code by 200 fold each.
- •We are attempting to use FPGAs to speed up Geant4 calculations.
- •FPGAs scale, use little power, and have high precision.
- •We show the issues involved in porting Geant4 to FPGA code and possible solutions.
Abstract
Amongst the scientific frameworks powered by the Monte Carlo (MC) toolkit Geant4 (Agostinelli
et al., 2003), the TOPAS (Tool for Particle Simulation) (Perl et al., 2012) is one.
TOPAS focuses on providing ease of use, and has significant implementation in the
radiation oncology space at present. TOPAS functionality extends across the full capacity
of Geant4, is freely available to non-profit users, and is being extended into radiobiology
via TOPAS-nBIO (Ramos-Mendez et al., 2018). A current “grand problem” in cancer therapy
is to convert the dose of treatment from physical dose to biological dose, optimized
ultimately to the individual context of administration of treatment. Biology MC calculations
are some of the most complex and require significant computational resources. In order
to enhance TOPAS’s ability to become a critical tool to explore the definition and
application of biological dose in radiation therapy, we chose to explore the use of
Field Programmable Gate Array (FPGA) chips to speedup the Geant4 calculations at the
heart of TOPAS, because this approach called “Reconfigurable Computing” (RC), has
proven able to produce significant (around 90x) (Sajish et al., 2012) speed increases
in scientific computing. Here, we describe initial steps to port Geant4 and TOPAS
to be used on FPGA.
We provide performance analysis of the current TOPAS/Geant4 code from an RC implementation
perspective. Baseline benchmarks are presented. Achievable performance figures of
the subsections of the code on optimal hardware are presented; Aspects of practical
implementation of “Monte Carlo on a chip” are also discussed.
Keywords
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Article info
Publication history
Published online: July 16, 2019
Accepted:
June 29,
2019
Received in revised form:
May 21,
2019
Received:
January 29,
2019
Identification
Copyright
Published by Elsevier Ltd on behalf of Associazione Italiana di Fisica Medica.
