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Need to understand how WebNN supports implementation that involves multiple devices and timelines #350

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wchao1115 opened this issue Feb 17, 2023 · 1 comment

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@wchao1115
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wchao1115 commented Feb 17, 2023

During the conversation on WebNN and WebGPU interop session, at the WebGPU F2F meeting in San Francisco, Myles Maxfield made an observation about the fact that WebNN MLContext is a single-device context. He raised the awareness that Apple's CoreML can distribute a workload within a single ML graph across multiple devices including the ANE, and said that it would be nice if WebNN has a provision to support that situation as well.

I think this feedback is related to a discussion in the working group of late about ways to create a notion of a default MLContext (when there is no explicit device associated with the context -- either a CPU device or a WebGPU device) that is more open to the implementation. This default context could effectively be whatever the implementer wants it to be including a multi-device context in the case of the Apple's WebKit implementation over CoreML.

@plehegar
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See also Device Selection Explainer and #809

inexorabletash added a commit to inexorabletash/webnn that referenced this issue Feb 13, 2025
- remove MLDeviceType and related prose
- update "create a context" algorithm
- be explicit MLContextOptions is a hint

Closes webmachinelearning#302, closes webmachinelearning#350, closes webmachinelearning#749

Signed-off-by: Zoltan Kis <[email protected]>
Co-authored-by: Joshua Bell <[email protected]>
Co-authored-by: Anssi Kostiainen <[email protected]>
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