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Hardware for meshing

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Old   March 2, 2017, 10:40
Default Hardware for meshing
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I'm currently thinking of getting a new computer for meshing purposes. The computer - which would be a laptop in optimal case - would not be used for actual calculations as powerful servers dedicated for some serious number crunching are available. Post-processing, however, would be done with the new computer. Used softwares would be Gambit, Meshing, ICEM, and maybe also SnappyHexMesh. The OS would be either windows or linux.

I have found quite many threads and posts concerning hardware requirements but they usually consider the actual CFD calculations instead of meshing, and I'm not sure whether the requirements for these processes are identical. I would like to hear your comments on the topic, if you would have more insight on the topic.

I suppose I would need at least 16 GB of memory, but the choice of processor is more difficult. My gut says that at least four cores would be preferable. I read that hyper threading is not very effective in calculations but is that the case also with meshing?

Any thoughts or comments?
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Old   March 3, 2017, 03:33
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It depends on the expected mesh size. You might be able to do it on a laptop in one case or you need a machine with 128 GB of RAM in another case :-)
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Old   March 3, 2017, 04:01
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Thanks for the reply,

I guess I was a bit too vague in my description. I have been working with Meshing creating meshes of approximately 5-10 million computational cells. 16 GB has been sufficient for the task thus far although more memory wouldn't hurt .

I realize that there are no global solutions available but I feel that this topic is slightly in the shadow of the topic of "hardware in calculations", which is of course more critical in the CFD world. I guess I am interested in hearing if anyone would have some knowledge of how different meshing softwares utilize hardware. By evaluating different aspects of the meshing alternatives, I'm hoping to gain better understanding of the boundary conditions of creating meshes and hopefully to learn how to enhance the whole experience of preprocessing.
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