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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Hussain, S. Silva, R.C.P. Lowther, D.A. |
| Copyright Year | 1965 |
| Abstract | Design engineers are always looking for extra computational power to speed up the execution of their tasks. One way to achieve this speedup is to identify tasks with a high degree of parallelism and process them with graphic processing units (GPUs). GPUs are optimized to process such tasks efficiently and quickly in massive multicore hardware. The steps involved in a finite-element (FE) electromagnetic simulation are computationally very expensive. One such step is the communication between FE solver and the material loss model that takes place for all the elements in the mesh for each time step. This task is massively parallel and, thus, could be executed in a GPU. As an example, a physics-based material model, the Jiles–Atherton model, is implemented in a GPU to compute the |
| Sponsorship | IEEE Magnetics Society |
| Starting Page | 1 |
| Ending Page | 4 |
| Page Count | 4 |
| File Size | 707126 |
| File Format | |
| ISSN | 00189464 |
| Volume Number | 52 |
| Issue Number | 3 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2016-01-01 |
| Publisher Place | U.S.A. |
| Access Restriction | One Nation One Subscription (ONOS) |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Graphics processing units Computational modeling Mathematical model Finite element analysis Solid modeling Magnetic hysteresis Random access memory finite element method Graphic processing unit (GPUs) parallel processing iron loss Jiles-Atherton model |
| Content Type | Text |
| Resource Type | Article |
| Subject | Electronic, Optical and Magnetic Materials Electrical and Electronic Engineering |
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