Palabos Clause Samples

Palabos. Scaling behaviour of the Palabos-npFEM code, as it simulates a coupled fluid – Red Blood Cell system on a heterogeneous platform (fluid on CPU, blood cells on GPU). The graph shows weak scaling, and the size of the simulated blood volume (in micro-meters) is indicated for each data point.

Palabos. Palabos is a lattice-Boltzmann Method (LBM) solver, available as open source, and massively parallel. The team of Prof ▇▇▇▇▇▇▇ ▇▇▇▇▇▇▇ at University of Geneva (Switzerland) has specialised it to solve a number of relevant biomedical problems, including simulation of blood flow, and bone cement penetration during vertebroplasty. The software has specific features to deal with biomedical problems including tools to read medical images. Palabos was tested on CADMOS BlueGene/Q (EPFL), Baobab (UNIGE). Non-clinical research ✔ Clinical research ✔ Clinical decision support ✔ Drug discovery ✔ Design & optimisation ✔ In silico preclinical trials ✔ In silico clinical trials ✔ Personal health forecasting ✔ Contact email: ▇▇▇▇▇.▇▇▇▇@▇▇▇▇▇.▇▇ URL: ▇▇▇▇://▇▇▇.▇▇▇▇▇▇▇.▇▇▇ No detailed information available as users are not individually tracked.

Palabos. Palabos is Lattice Boltzmann Method (LBM) solver, available as open source, and massively parallel. The team of Prof ▇▇▇▇▇▇▇ ▇▇▇▇▇▇▇ at University of Geneva (CH) has specialised it to solve a number of relevant biomedical problems, including simulation of blood flow, and bone cement penetration during vertebroplasty. The software has specific features to deal with biomedical problems, reading medical images. Palabos was tested on CADMOS BlueGene/Q (Switzerland), UniGe Baobab (Switzerland). Palabos is actively developed and optimised for emerging exascale systems, and the associated optimisation work is detailed in Section 7 of D5.6 and in D2.3/4. Summarizing the effort done so far, we propose a novel high-performance computational framework for the simulation of fully resolved whole blood flow. The framework models blood constituents like red blood cells (RBCs) and platelets individually, including their detailed non-linear elastic properties and the complex interactions among them. These kinds of simulation are particularly challenging because the large number of blood cells (up to billions) stand in contrast with the major computational requirement of individual constituents. While classical approaches address this challenge through simplified structural modelling of the deformable bodies (e.g., through mass-spring systems), the present framework guarantees accurate physics, desirable numerical properties through a fully featured FEM model and computational efficiency at the same order as more simplified state-of-the-art models. So far, code optimisation was specially focused at the single node level, and HPC-Cloud capabilities were put to a test, from deployment up to managing complex workflows for the optimisation process. Future parallelisation efforts will focus on application of the Replica Computing (RC) pattern (see D2.3), as results obtained from the numerical experiments relies on gathering a statistically relevant number of data from a stochastic process. Computations linked to platelet deposition are suitable for execution on GPU platforms, allowing deployment of these computations on a hybrid supercomputer.