GPGPU-based High Performance Computation

[doyubkim]

Support GPGPU backend for faster computation. Ideally Nvidia CUDA, but OpenCL is another option.

[doyubkim]

This has been the most wanted feature for a long time. I think it is the right time to make some push on this issue, together with Issue #18.

This issue is not very different from Issue #18. In fact, the new architecture and API should be carefully designed so that the both goals can be achieved within a unified framework.

This requires some internal re-architecturing:

1. The computation code should be kernel-based rather than the current inline-based implementation. This means strict separation between high-level API set (such as solvers with OOP + functional interface) and low-level APIs (such as BLAS operations with C-style interface).
2. Existing data structures should be more abstract and agnostic to internal buffer types. Direct access and manipulations should be discouraged and must use the kernel-centric APIs.
3. Item 1 and 2 above should be achieved with minimal changes (ideally no breaking changes, but just a few additions) to the existing API.

My current (high-level) plan for the development is:

1. Prototype with simple solver (such as basic grid-based solver or particle solver) + CUDA/ISPC
2. Expand the prototype to more complicated solvers (such as FLIP or PCISPH).
3. Settle down both high and low-level API.
4. Prototype with other compute backend such as OpenCL, Metal, or Vulkan (but just one of them) and test the extensibility of the new API.
5. Finalize the API and all the implementation.

As you can see, the primary target backends are CUDA (for GPU) and ISPC (for CPU), and hopefully will add either one of OpenCL/Metal/Vulkan.

This will be a months-long effort and more like a set of multiple milestones, especially given that I'm doing this as a hobby with limited time + HW + etc. But it will be a fun project, and I really look forward seeing meaningful outcome in the end.

[vtgstudio]

... looking forward to this feature.

[danielwinkler]

Hi Doyub,
will this development process be available in the repository (e.g. dev branch or public fork)?

[doyubkim]

@danielwinkler, I will push the intermediate work to a dev branch. Current dev branch has some GL work which is the groundwork for this GPGPU effort.

[doyubkim]

This issue is now under development in gpu branch (together with Issue #31). Nothing really useful at the moment, but hoping to get SPH implementation out soon.

[akav]

Would it be worth looking at OpenACC as a stepping stone on the path to GPGPU acceleration? Only reason I mention this, is because I was thinking if this project might be of help to generate OpenACC directives for existing source tree: https://github.com/gleisonsdm/DawnCC-Compiler

[doyubkim]

Thanks for the suggestion, @akav ! OpenACC is an interesting approach since it will make the code more readable. I am already working on SPH solver with CUDA, but it would be interesting to compare OpenACC and CUDA implementations in the end.