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CUDA and COMSOL

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Dear all, I have a new NVIDIA Quadro GPU and I would like to use it to accelerate my simulations, is it possible to use it somehow?
I looked for some informations and it seems to me that CUDA it's still unsupported, does someone have any fresh news?

I think this would be a very nice feature to be implemented in the future since nearly all the competitors (ansys, abaqus, nastran etc...) can benefit of GPU acceleration

6 Replies Last Post 31.07.2017, 09:40 GMT-4
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Posted: 1 decade ago 27.11.2013, 06:29 GMT-5
+1!!!!!!!

yes, please integrate GPU solving. These days it's much easier to setup personal clusters and todays's GPU performance is astounding!
+1!!!!!!! yes, please integrate GPU solving. These days it's much easier to setup personal clusters and todays's GPU performance is astounding!

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Posted: 1 decade ago 27.11.2013, 06:54 GMT-5
I've talked extensively about this with the support.
Making a long story short, the problem with GPU performances is that they are NOT stable, so changing the physics, boudary conditions, geometry or whatever can give completely different results.
As far as I understood ( but I'm not affiliated with comsol in any way so this can be wrong) COMSOL decided not to support GPU processing because of those issues.
I've talked extensively about this with the support. Making a long story short, the problem with GPU performances is that they are NOT stable, so changing the physics, boudary conditions, geometry or whatever can give completely different results. As far as I understood ( but I'm not affiliated with comsol in any way so this can be wrong) COMSOL decided not to support GPU processing because of those issues.

Niklas Rom COMSOL Employee

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Posted: 1 decade ago 03.12.2013, 09:33 GMT-5
Hi, just some clarifications about this interesting subject:

It is not COMSOL's opinion that GPUs are unstable or
unreliable.

We are following the GPU hardware development closely and when we find that
GPUs become useful to solve problems in COMSOL, we will support them.

Currently we see a number of factors that limit the
usefulness of GPUs for solving COMSOL problems. The main solvers in COMSOL
are the direct solvers and the multigrid solvers.

The direct solvers are very useful to handle strongly coupled smaller size
multiphysics problems, but they also require a lot of memory. Currently,
dedicated general purpose GPUs have about 5-16 GB of internal memory. This
corresponds to small problem sizes for the direct solvers, in the range
where they do not yield a high scalablity on GPUs.

For larger size problems, where multigrid is most efficient, the current
memory available in GPUs is not sufficient. In addition, multigrid solvers
use direct solvers on the coarsest grid, which also means that the
scalability of the coarse grid problem is limited on GPUs.

kind regards
Niklas Rom


I've talked extensively about this with the support.
Making a long story short, the problem with GPU performances is that they are NOT stable, so changing the physics, boudary conditions, geometry or whatever can give completely different results.
As far as I understood ( but I'm not affiliated with comsol in any way so this can be wrong) COMSOL decided not to support GPU processing because of those issues.


Hi, just some clarifications about this interesting subject: It is not COMSOL's opinion that GPUs are unstable or unreliable. We are following the GPU hardware development closely and when we find that GPUs become useful to solve problems in COMSOL, we will support them. Currently we see a number of factors that limit the usefulness of GPUs for solving COMSOL problems. The main solvers in COMSOL are the direct solvers and the multigrid solvers. The direct solvers are very useful to handle strongly coupled smaller size multiphysics problems, but they also require a lot of memory. Currently, dedicated general purpose GPUs have about 5-16 GB of internal memory. This corresponds to small problem sizes for the direct solvers, in the range where they do not yield a high scalablity on GPUs. For larger size problems, where multigrid is most efficient, the current memory available in GPUs is not sufficient. In addition, multigrid solvers use direct solvers on the coarsest grid, which also means that the scalability of the coarse grid problem is limited on GPUs. kind regards Niklas Rom [QUOTE] I've talked extensively about this with the support. Making a long story short, the problem with GPU performances is that they are NOT stable, so changing the physics, boudary conditions, geometry or whatever can give completely different results. As far as I understood ( but I'm not affiliated with comsol in any way so this can be wrong) COMSOL decided not to support GPU processing because of those issues. [/QUOTE]

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Posted: 1 decade ago 04.12.2013, 05:15 GMT-5
Thank you, Niklas, for these very informative remarks. I've been asking myself this very question for quite some time (and even tried to run Comsol with the CudaBLAS libraries at some point).

Where I thought GPU support would be the most useful is the Particle Tracing module. Especially if there are no particle–particle interactions, this should be a highly parallelizeable problem. Then again, the specialized (competitor) software that we predominantly use for these kinds of simulations also doesn't support GPUs, so I guess I'm missing something.
Thank you, Niklas, for these very informative remarks. I've been asking myself this very question for quite some time (and even tried to run Comsol with the CudaBLAS libraries at some point). Where I thought GPU support would be the most useful is the Particle Tracing module. Especially if there are no particle–particle interactions, this should be a highly parallelizeable problem. Then again, the specialized (competitor) software that we predominantly use for these kinds of simulations also doesn't support GPUs, so I guess I'm missing something.

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Posted: 10 years ago 26.01.2015, 07:10 GMT-5
Hi, the CG-iterative solver is perfectly suited for GPUs. At least I would expect that Comsol support this particular CG-solver maybe even with a separate module. This will at least reduce the pure linear equation solution time drastically for such cases. Probably then, the major time would be consumed by the assemble stage.
Hi, the CG-iterative solver is perfectly suited for GPUs. At least I would expect that Comsol support this particular CG-solver maybe even with a separate module. This will at least reduce the pure linear equation solution time drastically for such cases. Probably then, the major time would be consumed by the assemble stage.

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Posted: 7 years ago 31.07.2017, 09:40 GMT-4

Hi, just some clarifications about this interesting subject:

It is not COMSOL's opinion that GPUs are unstable or
unreliable.

We are following the GPU hardware development closely and when we find that
GPUs become useful to solve problems in COMSOL, we will support them.

Currently we see a number of factors that limit the
usefulness of GPUs for solving COMSOL problems. The main solvers in COMSOL
are the direct solvers and the multigrid solvers.

The direct solvers are very useful to handle strongly coupled smaller size
multiphysics problems, but they also require a lot of memory. Currently,
dedicated general purpose GPUs have about 5-16 GB of internal memory. This
corresponds to small problem sizes for the direct solvers, in the range
where they do not yield a high scalablity on GPUs.

For larger size problems, where multigrid is most efficient, the current
memory available in GPUs is not sufficient. In addition, multigrid solvers
use direct solvers on the coarsest grid, which also means that the
scalability of the coarse grid problem is limited on GPUs.

kind regards
Niklas Rom


I've talked extensively about this with the support.
Making a long story short, the problem with GPU performances is that they are NOT stable, so changing the physics, boudary conditions, geometry or whatever can give completely different results.
As far as I understood ( but I'm not affiliated with comsol in any way so this can be wrong) COMSOL decided not to support GPU processing because of those issues.



Is this something that is looked upon as a possible way to go for this? Or is that kind of memory not fast enough?

www.amd.com/en-us/press-releases/Pages/amd-radeon-pro-2016jul25.aspx

kind regards
Mattias
[QUOTE] Hi, just some clarifications about this interesting subject: It is not COMSOL's opinion that GPUs are unstable or unreliable. We are following the GPU hardware development closely and when we find that GPUs become useful to solve problems in COMSOL, we will support them. Currently we see a number of factors that limit the usefulness of GPUs for solving COMSOL problems. The main solvers in COMSOL are the direct solvers and the multigrid solvers. The direct solvers are very useful to handle strongly coupled smaller size multiphysics problems, but they also require a lot of memory. Currently, dedicated general purpose GPUs have about 5-16 GB of internal memory. This corresponds to small problem sizes for the direct solvers, in the range where they do not yield a high scalablity on GPUs. For larger size problems, where multigrid is most efficient, the current memory available in GPUs is not sufficient. In addition, multigrid solvers use direct solvers on the coarsest grid, which also means that the scalability of the coarse grid problem is limited on GPUs. kind regards Niklas Rom [QUOTE] I've talked extensively about this with the support. Making a long story short, the problem with GPU performances is that they are NOT stable, so changing the physics, boudary conditions, geometry or whatever can give completely different results. As far as I understood ( but I'm not affiliated with comsol in any way so this can be wrong) COMSOL decided not to support GPU processing because of those issues. [/QUOTE] [/QUOTE] Is this something that is looked upon as a possible way to go for this? Or is that kind of memory not fast enough? http://www.amd.com/en-us/press-releases/Pages/amd-radeon-pro-2016jul25.aspx kind regards Mattias

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