【DGL分享直播预告】Amazon AI Lab王老板空降直播间带来精彩图深度学习分享

0 嘉宾介绍

Biography

Minjie Wang is an applied scientist in Amazon Shanghai AI Lab. He obtained his Ph.D. degree from New York University. 

His research focus is the interdisciplinary area of machine learning and system including building deep learning systems with high usability and performance, applying machine learning in system optimization. He is also an open-source enthusiast; founder and major contributor of several well-known open source projects such as MXNet, MinPy and DGL.

1 分享内容

Building Efficient Systems for Deep Learning on Graphs

Building Efficient Systems for Deep Learning on Graphs

Abstract:

Advancing research in the emerging field of deep graph learning requires new tools to support tensor computation over graphs. In this talk, I will present the design principles and implementation of Deep Graph Library (DGL). DGL distills the computational patterns of GNNs into a few generalized sparse tensor operations suitable for extensive parallelization. By advocating graph as the central programming abstraction, DGL can optimize them transparently. By cautiously adopting a framework-neutral design, DGL allows users to easily port and leverage the existing components across multiple deep learning frameworks. The evaluation shows that DGL has little overhead for small scales and significantly outperforms other popular GNN-oriented frameworks in both speed and memory efficiency when workloads scale up. DGL has been open-sourced and recognized widely by the community. I will then introduce two follow-up works based on DGL: 1) FeatGraph – a flexible and efficient kernel backend for graph neural network and 2) DGL-KE – a distributed system for training knowledge graph embedding at scale.

2 直播间信息

会议时间：2020/11/22 19:00-20:00

点击链接入会，或添加至会议列表：

https://meeting.tencent.com/s/vSN6a8NBeq2V

会议 ID：925 998 356

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