Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Simulating complex physical phenomena implies the manipulation of an important amount of data. In order to simulate very large simulation domains on a limited computing architecture, such as industrial infrastructures, solutions have to be proposed. , a new out-of-core method is introduced in order to perform fast physical simulations using a complex Lattice Boltzmann model (LBM) on a single-node multi-GPU (CUDA) architecture. GPU global memory generally is far lor than the CPU main memory, can be problematic for a large simulation domain. The objective of this paper is to propose an efficient method of data exchanges beten GPUs, the CPU main memory, which allows to perform fast complex simulations on large installations. The combination of this method with the massive parallelism of GPUs allows to keep good simulation performance. A complex simulation involving two physical components (water + air) is used in order to validate this method.
['Julien Duchateau', 'François Rousselle', 'Nicolas Maquignon', 'Gilles Roussel', 'Christophe Renaud']
I am writing a research paper on a idea An Out-of-Core Method for Physical Simulations on a Multi-GPU Architecture Using Lattice Boltzmann Method
[{"from": "human", "value": "I am writing a research paper on a idea An Out-of-Core Method for Physical Simulations on a Multi-GPU Architecture Using Lattice Boltzmann Method"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Simulating complex physical phenomena implies the manipulation of an important amount of data. In order to simulate very large simulation domains on a limited computing architecture, such as industrial infrastructures, solutions have to be proposed. , a new out-of-core method is introduced in order to perform fast physical simulations using a complex Lattice Boltzmann model (LBM) on a single-node multi-GPU (CUDA) architecture. GPU global memory generally is far lor than the CPU main memory, can be problematic for a large simulation domain. The objective of this paper is to propose an efficient method of data exchanges beten GPUs, the CPU main memory, which allows to perform fast complex simulations on large installations. The combination of this method with the massive parallelism of GPUs allows to keep good simulation performance. A complex simulation involving two physical components (water + air) is used in order to validate this method."}]