Description
Hi there,
I'm new to Ginkgo, but I'm quite interested in its potential for incorporation into my lab's CFD code. We research DG FE methods for large-scale simulations, particularly on multi-GPU systems. Currently, we handroll all of our solvers, but I'm interested in adapting our solver workflow to utilize high performance off the shelf math libraries targeted for GPUs, which is how I discovered Ginkgo.
I came across the IDR(s) solver and was very encouraged by its performance, both in memory utilization and robustness compared to GMRES:
https://icl.utk.edu/newsletter/presentations/2015/Ponce-IDR-Solver-for-MAGMA%20Sparse-Iter-Package-2015-05-15.pdf
https://icl.utk.edu/files/publications/2017/icl-utk-1369-2017.pdf
I notice that Ginkgo supports IDR(s), but I don't believe that the package currently features multi-GPU/distributed support for the IDR(s) solver? I'm wondering if this is a development objective, or if there are fundamental limitations about the algorithm that are keeping it from scaling to distributed systems.
In addition, I'm also interested in the ParILUT preconditioner. I use ILU a lot for smaller cases but would love to be able to use it on larger problems, especially on the GPU. In the above references, I also see that it appears to significantly enhance the performance of IDR(s). I'm wondering if there is a plan to port ParILUT to multi-GPU/distributed memory as well?
In summary, I'd like to solicit advice from you all on the following:
- What is your experience with IDR? It seems quite promising from the linked references, but I haven't seen it incorporated into any other packages like PETSc or Trilinos. Is this just because the IDR concept is still new and hasn't "taken off" yet, or have people observed lackluster performance in real problems and passed over it in lieu of established alternatives like GMRES?
- If so, would it be possible to port IDR to multi-GPU/distributed memory similar to the rest of the algorithms in the Ginkgo solver collection?
- The same for ParILUT?
I appreciate your time and look forward to hopefully incorporating Ginkgo into my research!