RT journal article
T1 Dynamic Load Balancing Strategy for Parallel Tumor Growth Simulations
A1 Salguero Hidalgo, Alberto Gabriel
A1 Tomeu Hardasmal, Antonio Jorge
A1 Capel, Manuel I.
A2 Ingeniería Informática
K1 Cellular Automaton
K1 High Performance Computing
K1 Mathematical Oncology
K1 Tumoral Growth Simulation
K1 Parallel Programming
AB In this paper, we propose a parallel cellular automaton tumor growth model that includes load balancing ofcells distribution among computational threads with the introduction of adjusting parameters. The obtainedresults show a fair reduction in execution time and improved speedup compared with the sequential tumorgrowth simulation program currently referenced in tumoral biology. The dynamic data structures of the modelcan be extended to address additional tumor growth characteristics such as angiogenesis and nutrient intakedependencies.
PB De Gruyter
SN 1613-4516
YR 2019
FD 2019-03
LK http://hdl.handle.net/10498/21325
UL http://hdl.handle.net/10498/21325
LA eng
DS Repositorio Institucional de la Universidad de Cádiz
RD 13-nov-2026