JuliaApproximation / JuliaApproximation/FastTransforms.jl
GPU compatibility
Nobody has claimed this yet.
- Dominant language
- Julia
- Stars
- 281
- Forks
- 27
- PR merge metrics
- No merged PRs in 30d
Description
I wonder if it would be realistic and/or a goal to make the library GPU compatible. With that I mean only the crucial part of applying a pre-computed plan to a CUDA / CU Array.
This is probably a bit tricky in the c library. While the FFTW parts could probably be bound to the appropiate CUDA implementations (there is cuFFT), it would need adjustments for the other plans. Personally I have no experience with CUDA in C, but in Julia a bit and looked at the old pure version of the SH plans and it seemed at least plausible that this would be doable there, but maybe I also overlooked something.
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Research direction
No files, tests, or entry points are named. Start by mapping the C library's plan-application path and its FFTW dependencies, then assess whether cuFFT and the other plan operations can support CUDA/CU arrays. Done requires a defined GPU-compatible scope and a validated implementation for applying pre-computed plans.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- c, julia
- Domain
- backend, performance
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100