Szczegóły publikacji
Opis bibliograficzny
Continuous and discrete models of melanoma progression simulated in multi-GPU environment / Witold DZWINEL, Adrian KŁUSEK, Rafał WCISŁO, Marta PANUSZEWSKA, Paweł TOPA // W: Parallel Processing and Applied Mathematics : 12th international conference, PPAM 2017 : Lublin, Poland, September 10–13, 2017 : revised selected papers, Pt. 1 / eds. Roman Wyrzykowski [et al.]. — Cham: Springer International Publishing, cop. 2018. — (Lecture Notes in Computer Science ; ISSN 0302-9743 ; LNCS 10777. Theoretical Computer Science and General Issues ; ISSN 0302-9743). — ISBN: 978-3-319-78023-8; e-ISBN: 978-3-319-78024-5. — S. 505–518. — Bibliogr. s. 517–518, Abstr.
Autorzy (5)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 113577 |
|---|---|
| Data dodania do BaDAP | 2018-05-17 |
| DOI | 10.1007/978-3-319-78024-5_44 |
| Rok publikacji | 2018 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Wydawca | Springer |
| Konferencja | Parallel Processing and Applied Mathematics : 12th international conference |
| Czasopisma/serie | Lecture Notes in Computer Science, Theoretical Computer Science and General Issues |
Abstract
Existing computational models of cancer evolution mostly represent very general approaches for studying tumor dynamics in a homogeneous tissue. Here we present two very different cancer models: the heterogeneous continuous/discrete and purely discrete one, focusing on a specific cancer type - melanoma. This tumor proliferates in a complicated heterogeneous environment of the human skin. The results from simulations obtained for the two models are confronted in the context of their possible integration into a single multi-scale system. We demonstrate that the interaction between the tissue - represented by both the concentration fields (the continuous model) and the particles (the discrete model) - and the discrete network of blood vessels is the crucial component, which can increase the simulation time even one order of magnitude. To compensate this time lag, we developed GPU/CUDA implementations of the two melanoma models. Herein, we demonstrate that the continuous/discrete model, run on a multi-GPU cluster, almost fifteen times outperforms its multi-threaded CPU implementation.