Power Consumption Comparison of GPU Linear Solvers for Cellular Potts Model Simulations
Source abstract
Abstract
Power consumption is a significant challenge in the sustainability of computational science. The growing energy demands of increasingly complex simulations and algorithms lead to substantial resource use, which conflicts with global sustainability goals. This paper investigates the energy efficiency of different parallel implementations of a Cellular Potts model, which models cellular behavior through Hamiltonian energy minimization techniques, leveraging modern GPU architectures. By evaluating alternative solvers, it demonstrates that specific methods can significantly enhance computational efficiency and reduce energy use compared to traditional approaches. The results confirm notable improvements in execution time and energy consumption. In particular, the experiments show a reduction in terms of power of up to 53%, providing a pathway towards more sustainable high-performance computing practices for complex biological simulations.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Cellular Automata and Applications · Lattice Boltzmann Simulation Studies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
International PhD Programme/UNESCO Chair “Environment, Resources and Sustainable Development”, Department of Science and Technology, Parthenope University of Naples, Centro Direzionale Isola C4, 80143 Naples, Italy
Department of Science and Technology, Parthenope University of Naples, Centro Direzionale Isola C4, 80143 Naples, Italy
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