Chao and I are working on compressing gradients to low bit precision (2bit for now) to reduce communication costs and hence speedup training, especially for distributed training. The idea is to retain the compression error as residual and incorporate it into later iterations, so we don't see much (or any?) loss in accuracy.
Regards, Rahul On Wed, 27 Sep 2017 at 07:20 kellen sunderland <[email protected]> wrote: > Pedro and I are focusing on a few use cases involving mobile and IoT device > development. At the moment we're trying to run machine translation and > object detection models on a Jetson TX2 with reasonable performance. We'll > probably also look at a few different types of model compression at some > point as well. I think we're also happy to chip in with bug fixes where we > can. > > -Kellen > > On Wed, Sep 27, 2017 at 3:58 PM, Dom Divakaruni < > [email protected]> wrote: > > > A couple of us are working on sparse support. Bhavin or Haibin, can you > > fill in more detail? > > > > Regards, > > Dom > > > > > > > On Sep 26, 2017, at 4:35 PM, Nan Zhu <[email protected]> wrote: > > > > > > I am essentially doing the same thing as in xgboost-spark > > > > > > DF based ML integration, etc. > > > > > > Get Outlook for iOS<https://aka.ms/o0ukef> > > > ________________________________ > > > From: Naveen Swamy <[email protected]> > > > Sent: Tuesday, September 26, 2017 4:20:25 PM > > > To: [email protected] > > > Subject: Re: What's everyone working on? > > > > > > Hi Nan Zhu, > > > > > > Thanks for the update. Curious to know what part of mxnet-spark are you > > > working on? > > > > > > I am also evaluating the integration of MXNet with Spark, planning to > > start > > > with PySpark and also looking into spark-deep learning-pipelines > > > <https://github.com/databricks/spark-deep-learning>. > > > > > > Thanks, Naveen > > > > > >> On Tue, Sep 26, 2017 at 4:06 PM, Nan Zhu <[email protected]> > > wrote: > > >> > > >> working on mxnet-spark, fixing some limitations in ps-lite....(busy > for > > >> daily job in these days, should be back next week) > > >> > > >>> On Tue, Sep 26, 2017 at 10:13 AM, YiZhi Liu <[email protected]> > > wrote: > > >>> > > >>> Hi Dominic, > > >>> > > >>> I'm working on 0.11-snapshot and we will soon have one. While the > > >>> stable release will be after that we change package name from > > >>> 'ml.dmlc' to 'org.apache'. > > >>> > > >>> 2017-09-27 0:04 GMT+08:00 Dominic Divakaruni < > > >> [email protected] > > >>>> : > > >>>> That's great, YiZhi. Workday uses the Scala package and was looking > > >> for a > > >>>> maven distro for v0.11. When do you think you'll have one up? > > >>>> > > >>>> On Tue, Sep 26, 2017 at 8:58 AM, YiZhi Liu <[email protected]> > > >> wrote: > > >>>> > > >>>>> I'm currently working on maven deploy for scala package. > > >>>>> > > >>>>> 2017-09-26 16:00 GMT+08:00 Zihao Zheng <[email protected]>: > > >>>>>> I’m working on standalone TensorBoard, https://github.com/dmlc/ > > >>>>> tensorboard <https://github.com/dmlc/tensorboard>, currently we’ve > > >>>>> support several features in original TensorBoard from TensorFlow in > > >> pure > > >>>>> Python without any DL framework dependency. > > >>>>>> > > >>>>>> Recently I’m trying to bring more features to this standalone > > >> version, > > >>>>> but seems not very trivial as it depends on TensorFlow. Any advice > > are > > >>>>> welcomed and looking for help. > > >>>>>> > > >>>>>> Thanks, > > >>>>>> Zihao > > >>>>>> > > >>>>>>> 在 2017年9月26日，下午1:58，sandeep krishnamurthy < > > >>> [email protected]> > > >>>>> 写道： > > >>>>>>> > > >>>>>>> I am currently working with Jiajie Chen (https://github.com/ > > >>> jiajiechen/) > > >>>>> on > > >>>>>>> building an automated periodic benchmarking framework to run > > >> various > > >>>>>>> standard MXNet training jobs with both Symbolic and Gluon > > >> interface. > > >>>>> This > > >>>>>>> framework will run following standard training jobs on a nightly > > >> and > > >>>>> weekly > > >>>>>>> basis helping us to track performance improvements or regression > > >>> early > > >>>>> in > > >>>>>>> the development cycle of MXNet. Both CPU and GPU instances are > used > > >>>>>>> capturing various metrics like training accuracy, validation > > >>> accuracy, > > >>>>>>> convergence, memory consumption, speed. > > >>>>>>> > > >>>>>>> To start with, we will be running Resnet50, Resnet152 on CIFAR > and > > >>>>>>> Synthetic Dataset. And, few more RNN and Bidirectional LSTM > > >> training > > >>>>> jobs. > > >>>>>>> > > >>>>>>> Thanks, > > >>>>>>> Sandeep > > >>>>>>> > > >>>>>>> > > >>>>>>> On Mon, Sep 25, 2017 at 8:00 PM, Henri Yandell < > [email protected]> > > >>>>> wrote: > > >>>>>>> > > >>>>>>>> Getting an instance of github.com/amzn/oss-dashboard setup for > > >>> mxnet. > > >>>>>>>> > > >>>>>>>> Hopefully useful to write custom metric analysis; like: "most > pull > > >>>>> requests > > >>>>>>>> from non-committer" and "PRs without committer comment". > > >>>>>>>> > > >>>>>>>> Hen > > >>>>>>>> > > >>>>>>>> On Mon, Sep 25, 2017 at 11:24 Seb Kiureghian < > [email protected]> > > >>>>> wrote: > > >>>>>>>> > > >>>>>>>>> Hey dev@, > > >>>>>>>>> > > >>>>>>>>> In the spirit of bringing more activity to the mailing lists > and > > >>>>> growing > > >>>>>>>>> the community, can everyone who is working on MXNet please > share > > >>> what > > >>>>>>>>> you're working on? > > >>>>>>>>> > > >>>>>>>>> I'm working on > > >>>>>>>>> -Redesigning the website > > >>>>>>>>> <https://mxnet.incubator.apache.org/versions/master/index.html > >. > > >>>>>>>>> -Setting up a forum for user support. > > >>>>>>>>> > > >>>>>>>>> Seb Kiureghian > > >>>>>>>>> > > >>>>>>>> > > >>>>>>> > > >>>>>>> > > >>>>>>> > > >>>>>>> -- > > >>>>>>> Sandeep Krishnamurthy > > >>>>>> > > >>>>> > > >>>>> > > >>>>> > > >>>>> -- > > >>>>> Yizhi Liu > > >>>>> DMLC member > > >>>>> Technical Manager > > >>>>> Qihoo 360 Inc, Shanghai, China > > >>>>> > > >>>> > > >>>> > > >>>> > > >>>> -- > > >>>> > > >>>> > > >>>> Dominic Divakaruni > > >>>> 206.475.9200 <(206)%20475-9200> Cell > > >>> > > >>> > > >>> > > >>> -- > > >>> Yizhi Liu > > >>> DMLC member > > >>> Technical Manager > > >>> Qihoo 360 Inc, Shanghai, China > > >>> > > >> > > >
