Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

How can I integrate this project API to TensorFlow or Caffe? #7

Closed
ysh329 opened this issue Mar 29, 2017 · 11 comments
Closed

How can I integrate this project API to TensorFlow or Caffe? #7

ysh329 opened this issue Mar 29, 2017 · 11 comments

Comments

@ysh329
Copy link

ysh329 commented Mar 29, 2017

Is there some tips or docs? Thanks a lot!

@AnthonyBarbier
Copy link
Contributor

Hi,

We're working on it but it's still early stages. We'll publish some blog posts and examples in the coming weeks / months.

@mikyoreyes
Copy link

Thank you

@ysh329
Copy link
Author

ysh329 commented Mar 29, 2017

@AnthonyARM
Thank you very much for your work! 👍
We will continue to focus on this repo.

@Thunderbob
Copy link

The licensing terms allow you to do this if you intend to do it yourself. We intend to integrate our library with Caffe and TensorFlow however this is still work in progress, so watch this space!

@bhack
Copy link

bhack commented Mar 30, 2017

I really hope that ARM can intergrate upstream like Intel.

@mikyoreyes
Copy link

Hi @Thunderbob! Will you be creating a repository for Caffe/Tensorflow with the ComputeLibrary?

@AnthonyBarbier
Copy link
Contributor

We're only getting started, we haven't decided yet how we were going to contribute to these projects

@psyhtest
Copy link

psyhtest commented Apr 1, 2017

As I contributed CLBlast support in Caffe, I see two options for optimising Caffe on ARM Mali GPUs when using the BLAS approach for computing convolutions:

  1. Implement all BLAS routines needed by Caffe in a partial Mali-optimised library (based on this released compute library) and provide its integration with Caffe similar to ISAAC.
  2. Provide a Mali-optimised plugin for CLBlast using a new plugin framework proposed by @intelfx. In fact, he already used the Mali-optimised SGEMM code that ARM released over a year ago for creating a Mali-optimised CLBlast overlay. (See this Jupyter notebook for performance improvements on Samsung Chromebook 2 with AlexNet and SqueezeNet 1.0; the overlay needed more work support GoogleNet and SqueezeNet 1.1.) The new framework should be more robust and allow to use Mali-optimised implementations on Android (where the LD_PRELOAD trick is not available).

I'm happy to provide further pointers and discuss.

@austingg
Copy link

austingg commented Apr 6, 2017

@psyhtest seems openblas works best

@psyhtest
Copy link

psyhtest commented Apr 6, 2017

@austingg Yes, but it was fairly optimised implementation on quad-core Cortex-A15 @ 1700 GHz vs unoptimised implementation on quad-core Mali-T628 @ 600 MHz...

@ManubARM
Copy link

ManubARM commented Feb 5, 2019

Closing for inactivity. Anyway to answer the initial question:

There is a project made exactly to solve this kind of problems: ArmNN
Here is the link to the repo:
https://github.com/ARM-software/armnn

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Projects
None yet
Development

No branches or pull requests

8 participants