Call for Presentations: Apache MXNet Day (Due 16 November 2020)

[Sheng Zha <zh...@apache.org>]

The Apache MXNet (incubating) podling Project Management Committee is
pleased to announce the Call for Presentations for Apache MXNet Day.

Hosted by The Apache Software Foundation, AWS, and NVIDIA, Apache
MXNet Day is an online, virtual event taking place on 14 December 2020
9AM - 5PM PST (UTC -8). We are now accepting submissions for 30-minute
talks in the following categories for Apache MXNet and:

- Research and applications
- Production and deployment
- Framework architecture and compiler technology
- Optimization and performance
- Distributed training

Please email your title and abstract (up to 600 words) to:
apachemxnetday@nvidia.com. Deadline is 12Noon PST (UTC -8) on Monday
16 November 2020.

Apache MXNet Day attendees will learn:

- All about the Apache MXNet ecosystem, including libraries, toolkits, and more
- How Apache MXNet compares to other deep learning frameworks
- How to overcome user challenges in research or production environments
- New MXNet features to improve performance and user experience
- MXNet project roadmap and future direction
- How to participate in and contribute to Apache MXNet

...as well as have the opportunity to meet the original developers of
Apache MXNet and key members of the Apache MXNet community, who will
be available to share the project's history and answer questions in a
friendly, collaborative environment.

Registration is FREE of charge and will open shortly. To be notified,
sign up to the Apache MXNet user list by sending an email to
user-subscribe@mxnet.apache.org

We look forward to seeing you!

Regards,
Sheng Zha for the Apache MXNet Podling Project Management Committee


About Apache MXNet (incubating) https://mxnet.apache.org/
Apache MXNet is an Open Source deep learning framework designed for
both efficiency and flexibility. It allows you to mix symbolic and
imperative programming to maximize efficiency and productivity. At its
core, MXNet contains a dynamic dependency scheduler that automatically
parallelizes both symbolic and imperative operations on the fly. A
graph optimization layer on top of that makes symbolic execution fast
and memory efficient. MXNet is portable and lightweight, scalable to
many GPUs and machines.

MXNet is more than a deep learning project. It is a community on a
mission of democratizing AI. It is a collection of blueprints and
guidelines for building deep learning systems, and interesting
insights of DL systems for hackers. It has been used for ResNet50
benchmarks due to its superior performance among different deep
learning frameworks ever since the debut of the MLPerf. It has been
adopted in many products from cloud to edge due to its high
performance, distributed training and portability. Free trained most
popular models can be found in GluonCV, GluonNLP, GluonTS, AutoGluon,
InsightFace, Sockeye, and DGL, which are trained with Apache MXNet as
backend. And new Gluon 2.0 will make it even more friendly for deep
learning researchers and practitioners.

Apache MXNet is an effort undergoing incubation at The Apache Software
Foundation (ASF), sponsored by the Apache Incubator. Incubation is
required of all newly accepted projects until a further review
indicates that the infrastructure, communications, and decision making
process have stabilized in a manner consistent with other successful
ASF projects. While incubation status is not necessarily a reflection
of the completeness or stability of the code, it does indicate that
the project has yet to be fully endorsed by the ASF.