srkreddy1238 commented on code in PR #13867: URL: https://github.com/apache/tvm/pull/13867#discussion_r1092853604
########## docs/how_to/deploy/adreno.rst: ########## @@ -65,134 +84,667 @@ Reasons of using textures: Overall, with textures, it is possible to achieve a significant performance boost compared to OpenCL buffer based solutions. -.. _building_tvm_for_adreno: +.. _about_openclml: + +About OpenCLML +-------------- + +OpenCLML is a SDK released by Qualcomm that provides accelerated deep learning operators. +These operators are exposed as an extension "cl_qcom_ml_ops" to standard OpenCL specification. +Please refer `Accelerate your models with our OpenCL ML SDK <https://developer.qualcomm.com/blog/accelerate-your-models-our-opencl-ml-sdk>`_ for more details. + +OpenCLML is integrated into TVM as a `BYOC <https://tvm.apache.org/docs/dev/how_to/relay_bring_your_own_codegen.html?highlight=bring%20your%20own>`_ solution. +OpenCLML operators can use same context and the operatrors can be enqueued on same command queue if native OpenCL. +We took advantage of this to avoid any context switching over heads while fallback to native OpenCL. + + +.. _build_deploy: + +TVM for Adreno™ Review Comment: Missed the deploy models part. I will restore it. Earlier the doc was more texture enhancement centric (too technical). Objective here is to simplify it in a way that a new user will have a good start with TVM and Adreno. Thanks for the suggestions, it make sense to separate theory and sample code. I will rearrange the same. Feel free to review and advice I want multiple opinions to perfect the docs. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
