Efficient model of tumor dynamics simulated in multi-GPU environment. (May 2019)

• Record Type: Journal Article
• Authors: Kłusek, Adrian; Łoś, Marcin; Paszyński, Maciej; Dzwinel, Witold
• Other Names: Mencagli Gabriele guest-editor.; França Felipe MG guest-editor.; Bentes Cristiana Barbosa guest-editor.; Justen Marzulo Leandro Augusto guest-editor.; Lima Pilla Mauricio guest-editor.; Wyrzykowski Roman guest-editor.; Deelman Ewa guest-editor.
• Is Part Of: International journal of high performance computing applications. Volume 33:Number 3(2019)
• Page Start: 489
• Page End: 506
• Publication Date: 2019-05
• Subjects: Tumor modeling -- continuous/discrete cancer model -- multi-GPU/CUDA implementation -- melanoma model -- tumor therapy model; High performance computing -- Periodicals; Supercomputers -- Periodicals; 004.1105
• DOI: 10.1177/1094342018816772
• Languages: English
• ISSNs: 1094-3420

Abstract

The application of computer simulation as a tool in predicting cancer dynamics (e.g. during anticancer therapy) requires tumor models, which are nontrivial and, simultaneously, not computationally demanding. To this end, both the level of details and computational efficiency of the model should be well balanced. The restrictions on computational time are forced by very demanding data assimilation process in the phase of parameters learning and their correction on the basis of incoming medical data. Herein we present a very efficient multi-GPU/CUDA implementation of three-dimensional (3-D) cancer model which allows for simulating both the growth and treatment phases of tumor dynamics. We demonstrate that the interaction between the tissue and the discrete network of blood vessels is a crucial component, which influences considerably the simulation time. Here we present a new solution which eliminates this flaw. We show also that the efficiency of our model does not depend on the complexity of tumor setup. As an example, we confront the growth of tumor in a simple and homogeneous environment with melanoma evolution, which proliferates in a complex environment of human skin. Consequently, the 3-D simulation of a tumor growth up to 1 cm in diameter requires an hour of computations on a midrange multi-GPU server.