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: [email protected]. 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 [email protected] 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.
