NPU Acceleration
Nobody has claimed this yet.
Assessment
- Difficulty
- 5/5
- Estimated time
- Over a week
- Newbie friendliness
- 25/100
- Issue type
- Feature
- Clarity
- Needs clarification
- Activity status
- Quiet
- Tech stack
- machine-learning
- Domain
- devops, machine-learning, operating-systems
Research direction
The issue names no files, tests, or entry points. Start by identifying the Windows Containers device pass-through implementation and its existing GPU limitations; done means documenting and implementing a defined approach for NPU acceleration in Windows Containers, with coverage for the supported AI/ML workload scenarios.
Written by the indexing model from the issue text.
Description
Currently, only a subset of devices can be passed through, with GPUs being one of them (albeit limited with only DirectX based frameworks).
With the rise and push of NPU/IPUs built into processors, it would be beneficial to provide NPU acceleration in Windows Containers to be able to containerize our AI/ML workloads.
- Dominant language
- PowerShell
- Stars
- 551
- Forks
- 76
- PR merge metrics
- No merged PRs in 30d
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
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