Towards Real Time Radiotherapy Simulation

Voss, Nils; Ziegenhein, Peter; Vermond, Lukas; Hoozemans, Joost; Mencer, Oskar; Oelfke, Uwe; Luk, Wayne; Gaydadjiev, Georgi

doi:10.1109/asap.2019.000-6

Cited by 2 publications

(1 citation statement)

References 23 publications

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“…This work presents an extension to [23]. Most notably we extend the implementation to also use a Xilinx Alveo U250 card and provide a significantly more detailed evaluation.…”

Section: Monte Carlo Dose Simulationmentioning

confidence: 99%

Towards Real Time Radiotherapy Simulation

Voss

Ziegenhein

Vermond

et al. 2020

J Sign Process Syst

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We propose a novel reconfigurable hardware architecture to implement Monte Carlo based simulation of physical dose accumulation for intensity-modulated adaptive radiotherapy. The long term goal of our effort is to provide accurate dose calculation in real-time during patient treatment. This will allow wider adoption of personalised patient therapies which has the potential to significantly reduce dose exposure to the patient as well as shorten treatment and greatly reduce costs. The proposed architecture exploits the inherent parallelism of Monte Carlo simulations to perform domain decomposition and provide high resolution simulation without being limited by on-chip memory capacity. We present our architecture in detail and provide a performance model to estimate execution time, hardware area and bandwidth utilisation. Finally, we evaluate our architecture on a Xilinx VU9P platform as well as the Xilinx Alveo U250 and show that three VU9P based cards or two Alevo U250s are sufficient to meet our real time target of 100 million randomly generated particle histories per second.

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“…This work presents an extension to [23]. Most notably we extend the implementation to also use a Xilinx Alveo U250 card and provide a significantly more detailed evaluation.…”

Section: Monte Carlo Dose Simulationmentioning

confidence: 99%

Towards Real Time Radiotherapy Simulation

Voss

Ziegenhein

Vermond

et al. 2020

J Sign Process Syst

Self Cite

View full text Add to dashboard Cite

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Efficient Table-Based Polynomial on FPGA

Barbone

Kwaadgras

Oelfke

et al. 2021

2021 IEEE 39th International Conference on Computer Design (ICCD)

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Field Programmable Gate Arrays (FPGAs) are gaining popularity in the context of scientific computing due to the recent advances of High-Level Synthesis (HLS) toolchains for customised hardware implementations combined with the increase in computing capabilities of modern FPGAs. As a result, developers are able to implement more complex scientific workloads which often require the evaluation of univariate numerical functions. In this study, we propose a methodology for tablebased polynomial interpolation aiming at producing area-efficient implementations of such functions on FPGAs achieving the same accuracy and at similar performance as direct implementations. We also provide a rigorous error analysis to guarantee the correctness of the results. Our methodology covers the forecast of resource utilisation of the polynomial interpolator and, based on the characteristics of the function, guides the developer to the most area-efficient FPGA implementation. Our experiments show that in the case of a radiation spectrum of a Black Body application based on evaluating Planck's Law, it is possible to reduce resource utilisation by up to 90% when compared to direct implementations not using table-based methods. Moreover, when only the kernels are considered, our method uses up to two orders of magnitude fewer resources with no performance penalties. Based on previous more theoretical works, our study investigates practical applications of table-based methods in the context of high performance and scientific computing where it is used to implement common but more complex functions than the elementary functions widely studied in the related literature.

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Towards Real Time Radiotherapy Simulation

Cited by 2 publications

References 23 publications

Towards Real Time Radiotherapy Simulation

Towards Real Time Radiotherapy Simulation

Efficient Table-Based Polynomial on FPGA

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