[RFC]: DLPack C Function for Speed Exchange

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#973 2 comments 2 reactions 0 assignees View on GitHub

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Assessment

Difficulty
5/5
Estimated time
Over a week
Newbie friendliness
25/100
Issue type
Feature
Clarity
Mostly clear
Activity status
Stale
Tech stack
c, python
Domain
api, performance

Research direction

Start by reading the linked DLPack issue 175 and the current DLPack exchange context. Define how the proposed mypackage.Tensor.__dlpack_c_exchange_api__ field should be standardized for array libraries, including its relationship to the existing Python exchange and fallback behavior; the work is done when the RFC has an agreed specification.

Written by the indexing model from the issue text.

Description

API extension Needs Discussion RFC topic: Device Handling topic: DLPack

This is a cross ref RFC on DLPack based exchange. As of now, DLPack exchange relies on python functions such as tensor.__dlpack__(). While they works well for common cases, the general overhead of such exchange is at the level of 0.2-0.3 us for very well optimized version, and can go up to 0.4-1 us for less optimized implementation.

For a function that takes three arguments f(a, b, c), assume we run DLPack exchange for each argument, the general conversion overhead usually gets to around 0.7us - 3us.

While such overhead can be acceptable in many settings, in GPU applications the extra 1-3us overhead can still be significant. For a kernel that takes 2us to finish, 0.7 us means 30% additional overhead in execution

Recently, we propose to develop a set of specific C functions to help DLPack based exchange for array libraries that works on C extensions, please see more context here

https://github.com/dmlc/dlpack/issues/175

In the context of array-api, it would be useful to help standardize the specific field for such speed exchange

  • mypackage.Tensor.__dlpack_c_exchange_api__

Note that the proposed speed exchange function can be used in conjunction with the current DLPack exchange, to gracefully handle fallback cases.

Dominant language
Python
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Forks
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