This project aims at implementing a GPU accelerated non-linear solver for hyperelastic neo- Hookian models with contact. The project will build on the PolyFEM [11], a C++ and Python finite element library (https://polyfem.github.io/), coupled with the Incremental potential contact method which allows accurate simulation of surface-to-surface contact (https://ipc- sim.github.io/). Currently, PolyFEM relies on multithreading libraries like TBB, the strategy is to reengineer the non-linear solver section of the code to make it suitable for CUDA [10] device functions taking advantage of libraries such as cuBLAS, cuSPARSE, Thrust and external sparse linear solvers with GPU support. Our goal is to obtain a performance improvement of stress tests in comparison with multithreading implementation from low to high end CPUs. The project will be conducted in collaboration with Teseo Schneider (University of Victoria).

GPU accelerated contact simulations(2022 Dec 20).

GPU accelerated contact simulations

-
2022-12-20

Abstract

This project aims at implementing a GPU accelerated non-linear solver for hyperelastic neo- Hookian models with contact. The project will build on the PolyFEM [11], a C++ and Python finite element library (https://polyfem.github.io/), coupled with the Incremental potential contact method which allows accurate simulation of surface-to-surface contact (https://ipc- sim.github.io/). Currently, PolyFEM relies on multithreading libraries like TBB, the strategy is to reengineer the non-linear solver section of the code to make it suitable for CUDA [10] device functions taking advantage of libraries such as cuBLAS, cuSPARSE, Thrust and external sparse linear solvers with GPU support. Our goal is to obtain a performance improvement of stress tests in comparison with multithreading implementation from low to high end CPUs. The project will be conducted in collaboration with Teseo Schneider (University of Victoria).
Heltai, Luca
Schneider, Teseo
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11767/130795
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