Agree, this time is available for me.
On 2020/4/15 上午11:42, Shanshishi wrote:
I suggest to hold the meeting every two weeks at 14:30-16:30 on Monday.
-----邮件原件----- 发件人: Xiehong (Cynthia) via A-tune [mailto:a-tune@openeuler.org] 发送时间: 2020年4月15日 11:27 收件人: zhangmiao zhangmiao@iscas.ac.cn; Xiezhipeng (EulerOS) xiezhipeng1@huawei.com; a-tune@openeuler.org 主题: [A-tune] 答复: 答复: Re: Glad to join a-tune group and need more information
Hi
You can propose several time which are suitable for you. Then we can choose one for all of us. .Best regards
Cynthia Xie
-----邮件原件----- 发件人: zhangmiao [mailto:zhangmiao@iscas.ac.cn] 发送时间: 2020年4月15日 11:10 收件人: Xiehong (Cynthia) xiehong@huawei.com; Xiezhipeng (EulerOS) xiezhipeng1@huawei.com 抄送: a-tune@openeuler.org 主题: Re: 答复: [A-tune] Re: Glad to join a-tune group and need more information
Hello xiehong，
It is of course very helpful if a routing meeting can be held for this SIG.
but a-tune developers' busy work should also be considered.
a proper period should be selected carefully.
On 2020/4/14 下午9:49, Xiehong (Cynthia) wrote:
Hi all Is it possible to arrange a routing voice meeting for this SIG? It seems more efficient to discuss via voice meeting.
Best regards
Cynthia Xie
-----邮件原件----- 发件人: Xiezhipeng (EulerOS) via A-tune [mailto:a-tune@openeuler.org] 发送时间: 2020年4月14日 21:35 收件人: zhangmiao zhangmiao@iscas.ac.cn 抄送: a-tune@openeuler.org 主题: [A-tune] Re: Glad to join a-tune group and need more information
Hi,zhangmiao
I think these todos can be separated to 3 parts
1. framework enhancement, e.g. Automatic Bottleneck Detection
- algorithm enhancement, e.g. Unsupervised and semi-supervised
Classification Algorithm
- more workload type support, e.g More Platforms Support
Am I understand it properly?
More Platforms Support Refers to more hardware support.
Is it possible to share your priority plan and milestone of the todo list? e.g the target of 2020 2nd quarter, 3rd quarter, 4th quarter?
Sorry, such a detailed target plan is currently not available. Our goal is to make performance tuning more efficient. This year we plan to make the tuning function smarter.
Our current priority is making some currently known performance optimization methods integrated into the A-Tune project Some ideas in TODO will be reinvested when appropriate in the future, of course, interested developers are welcome to implement some of them in advance.
Is there any other open-source projects, papers, or ideas is used as references , or is there any conferences that you are following, when developing a-tune project ?
We have analyzed some papers about performance tuning and AI. Maybe we can put some public paper links in the readme later :)
Thanks, Zhipeng Xie
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