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From "Lv, Tao A" <tao.a...@intel.com>
Subject RE: Cambricon MLU support for MXNet.
Date Mon, 17 Dec 2018 13:47:35 GMT
"mshadow is being deprecated." 

Surprised to know that. Was it discussed before? Do we have any document to tell contributors
and developers about that?

-tao

-----Original Message-----
From: Chris Olivier [mailto:cjolivier01@gmail.com] 
Sent: Monday, December 17, 2018 3:10 PM
To: dev@mxnet.incubator.apache.org; ??? <zhanghaochong@cambricon.com>
Cc: dev@mxnet.apache.org; solomon.zhc <solomon.zhc@gmail.com>
Subject: Re: Cambricon MLU support for MXNet.

small point: mshadow is being deprecated. probably you shouldn’t invest too much time on
it. just an FYI

On Sun, Dec 16, 2018 at 6:33 PM 张昊翀 <zhanghaochong@cambricon.com> wrote:

> Dear MXNet community,
>
> We are from Cambricon, a leading supplier of artificial intelligence 
> chips. We have two product lines, including IP products (e.g., 
> Cambricon
> 1A/1H) and chip products (e.g., MLU100 released in May 2018)
>
> We are now adapting MXNet on Cambricon products. During the follow-up 
> session, we plan to open source, and hope to merge these new features 
> into the master branch of MXNet and to be a part of MXNet's long-term support.
> We firmly believe that these MLU features will promote the MXNet 
> community development.
> To this end, we are ready to accept the rigorous inspection of MXNet 
> community. In addition, we need advice from the community to achieve 
> high quality implementation. On this basis, we very much hope to reach 
> a full-scale long-term cooperation with the community.
>
> In order to achieve the above goals, we hope to keep in touch with the 
> community on some issues. Looking forward to your valuable feedback.
>
> 1. MLU100 mainly focuses on inference, and we plan to first support 
> the inference part of MXNet. The training part of MXNet on MLU will be 
> released in the future. Is that acceptable for MXNet community?
>
> 2. Though MLU can support various operators/networks, to guarantee 
> high quality, all supported operators submitted to the community 
> should undergo rigorous stress test. Thus, at the beginning, we plan 
> to release a small number of supported operators and networks, and 
> more of them will be continuously added. Is that acceptable or do we 
> have to support all networks in the ModelZoo in the first release?
>
> 3. Currently we plan to support both Python and C++ APIs. More details 
> on supported APIs will be provided in a follow-up proposal.
>
> 4. We need to modify the mShadow in order to support tensor memory 
> operations.
>
> 5. In order to enable the community to run and fully test our code, we 
> want to provide the community with a complete test environment. At 
> present, we are considering the following three ways.
> A) Provides several remote servers for community and integrates with 
> the community's Jenkins.
> B) Provide a cloud platform to the community.
> C) Donate MLU100 to the community's testing platform. However, we 
> don’t know the specific ways of donation, and we hope to get help. We 
> are wondering about how MXNet's test servers are managed.
>
> About more technical details, a proposal will be submitted to the 
> community before releasing the code.
>
> In addition to the above points, the remaining questions and 
> suggestions are also welcome. Thanks!
>
> More about Cambricon:
> Cambricon is the artificial intelligence computing pioneer that 
> engineers and successfully commercializes world’s first dedicated 
> machine learning processor. To bring its unique AI processors from 
> edge to cloud, enriching and advancing human life, is the firm mission 
> of the company. Dr. Tianshi Chen is the founder and CEO of Cambricon, 
> where he brings over 10 years experience in the fields of 
> micro-processor architecture and artificial intelligence.
> In 2016, Cambricon released Cambricon 1A processor, the first 
> commercial machine learning specific processor in the world. Later, 
> during the 3rd World Internet Conference, Cambricon 1A processor was 
> elected as one of “World Leading Internet Scientific and Technological 
> Achievements“. In May 2018, Cambricon released MLU100, a machine 
> learning chip which is in mass production now. By offering 
> revolutionary technology and products, Cambricon has established and 
> remains active relationships with various companies in the AI industry.
>
>
> Regards,
> Haochong Zhang
> Cambricon MXNet Development Team
>
>
>
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