Analysis of heterogeneous computing approaches to simulating heat transfer in heterogeneous material
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| Publicado en: | arXiv.org (May 18, 2019), p. n/a |
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| Autor principal: | |
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Cornell University Library, arXiv.org
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| Acceso en línea: | Citation/Abstract Full text outside of ProQuest |
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| 001 | 2228404537 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 2331-8422 | ||
| 035 | |a 2228404537 | ||
| 045 | 0 | |b d20190518 | |
| 100 | 1 | |a Loeb, Andrew | |
| 245 | 1 | |a Analysis of heterogeneous computing approaches to simulating heat transfer in heterogeneous material | |
| 260 | |b Cornell University Library, arXiv.org |c May 18, 2019 | ||
| 513 | |a Working Paper | ||
| 520 | 3 | |a The simulation of heat flow through heterogeneous material is important for the design of structural and electronic components. Classical analytical solutions to the heat equation PDE are not known for many such domains, even those having simple geometries. The finite element method can provide approximations to a weak form continuum solution, with increasing accuracy as the number of degrees of freedom in the model increases. This comes at a cost of increased memory usage and computation time; even when taking advantage of sparse matrix techniques for the finite element system matrix. We summarize recent approaches in solving problems in structural mechanics and steady state heat conduction which do not require the explicit assembly of any system matrices, and adapt them to a method for solving the time-depended flow of heat. These approaches are highly parallelizable, and can be performed on graphical processing units (GPUs). Furthermore, they lend themselves to the simulation of heterogeneous material, with a minimum of added complexity. We present the mathematical framework of assembly-free FEM approaches, through which we summarize the benefits of GPU computation. We discuss our implementation using the OpenCL computing framework, and show how it is further adapted for use on multiple GPUs. We compare the performance of single and dual GPUs implementations of our method with previous GPU computing strategies from the literature and a CPU sparse matrix approach. The utility of the novel method is demonstrated through the solution of a real-world coefficient inverse problem that requires thousands of transient heat flow simulations, each of which involves solving a 1 million degree of freedom linear system over hundreds of time steps. | |
| 653 | |a Sparsity | ||
| 653 | |a Thermodynamics | ||
| 653 | |a Assembly | ||
| 653 | |a Parallel processing | ||
| 653 | |a Finite element method | ||
| 653 | |a Simulation | ||
| 653 | |a Computation | ||
| 653 | |a Conductive heat transfer | ||
| 653 | |a Graphics processing units | ||
| 653 | |a Inverse problems | ||
| 653 | |a Conduction heating | ||
| 653 | |a Matrix methods | ||
| 653 | |a Electronic components | ||
| 653 | |a Heat transmission | ||
| 653 | |a Exact solutions | ||
| 653 | |a Mathematical models | ||
| 653 | |a Degrees of freedom | ||
| 653 | |a Domains | ||
| 653 | |a Computer simulation | ||
| 653 | |a Computer memory | ||
| 700 | 1 | |a Earls, Christopher | |
| 773 | 0 | |t arXiv.org |g (May 18, 2019), p. n/a | |
| 786 | 0 | |d ProQuest |t Engineering Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/2228404537/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full text outside of ProQuest |u http://arxiv.org/abs/1905.07622 |