ACM SIGCOMM 2018 Workshops and Tutorials: Friday Early Morning Session

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Abstract: In this talk, I will try to bridge two seemly remote areas, system/networking and machine learning, together. In the first part, I will present our on-going journey of building highly-available cloud systems, by leveraging the power of machine learning algorithms for failure detection and localization. Specifically, I will focus on the Deepview project which uses machine learning techniques for VM VHD failure localization. In the second part, I will present how a renewed networking technique, RDMA, can be used to scale and accelerate machine learning training. Through these two projects, I hope to demonstrate that the marriage of system/networking and machine learning are much desired and inevitable. We need machine learning to bring more intelligence into large-scale systems and to further improve system availability, and we need the principles and techniques from system and networking to accelerate machine learning algorithms at scale. Through the interactions of system/networking and machine learning, more intelligent and highly available cloud and ML systems can be built in the near future.

 

Bio: Chuanxiong Guo is a Director of the AI Lab of Bytedance. Before that, he was a Principal Researcher at Microsoft Research Redmond. He spent several years in Microsoft Azure as a Principal Software Engineering Manager. He was a Senior Researcher at Microsoft Research Asia before he joined Microsoft Azure. His areas of interest include networked systems at large-scale, data center networking, cloud computing, systems availability and troubleshooting. He is among the first to start data center networking research. He has won several best paper awards for his research in data center networking. Several of his envisions including DCN virtualization, DCN monitoring, and ServerSwitch generated both academic and industrial impacts. Many of the systems that he has designed and implemented, including RDMA/RoCEv2 and Pingmesh are deployed in Microsoft production data centers, are running in millions of servers in data centers, and widely adopted by the cloud computing industry.

 

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Bio: Anja Feldmann studied computer science at Universitaet Paderborn in Germany and received my degree in 1990. After that Anja continued her studies at Carnegie Mellon University, where she earned her M.Sc. in 1991 and, four years later, her Ph.D. The next four years she did postdoctoral work at AT&T Labs Research, before holding research positions at Saarland University and the Technical University Munich. Since 2006, Anja has been professor of Internet Network Architectures at Telekom Innovation Laboratories at Technische Universitaet Berlin. In May 2012, she was elected the first woman on the employer side of the Supervisory Board of SAP. Since the beginning of 2018 she is director at the Max Planck Institute for Informatics in Saarbruecken.

 

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Bio: Dr. Arianne Hinds is a Principal Architect at CableLabs where she is a video and immersive experience (VR/AR/MR) subject matter expert. Her primary responsibility is to help CableLabs’ members develop their roadmaps for deploying new services for immersive media and technologies. She holds the position of INCITS L3.1 Chairman, for which she is the head of the U.S. delegation of experts that participate in the Moving Picture Experts Group (MPEG). Arianne received her M.Sc. and Ph.D. degrees in Computer Science at the University of Colorado, Boulder in 2000 and 2007 respectively.