[FEA] Move PartDescriptor & Data abstractions from cuML
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- Dominant language
- Cuda
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Description
These abstractions have been used in the Dask packages of cuML to enable the representation of Dask partitions as input to our multi-node multi-GPU algorithms w/ the communicator. It would be useful for these abstractions to be placed in RAFT in order to create a more unified API for the inputs to primitives.
It would also be nice to include some Cython code for constructing and managing instances of PartDescriptor in order to ease the boilerplate needed and reduce duplication across primitives.
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- Read the whole issue, then the project's contributing guide.
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Research direction
No files or tests are named. Start by locating the PartDescriptor and Data abstractions in cuML's Dask packages, then inspect how RAFT primitives represent inputs and use the communicator. Define the scope for moving the abstractions and adding Cython construction and management, then verify affected multi-node, multi-GPU primitives use the unified API.
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Assessment
- Tech stack
- python
- Domain
- distributed-systems, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 20/100