Hardware- and Network-Enhanced Software Systems for Cloud Computing

Alexander L. Wolf

Dean of the Baskin School of Engineering, Univeristy of California, Santa Cruz

Abstract: The dominant approach in offering cloud services today continues to be based on homogeneous commodity resources: large numbers of inexpensive machines, interconnected by off-the-shelf networking equipment, supported by stock disk drives. However, both cloud users and cloud service providers have begun to recognize that this platform is unable to satisfy the requirements of many important and high-value classes of applications, such as those in the geosciences, interactive business analytics, and non-traditional map/reduce data processing tasks. 

This talk introduces the HARNESS project, a European effort aimed at exploring how to bring innovative and heterogeneous resources into cloud platforms. HARNESS disrupts the existing cloud software stack by considering the impact of technologies such as field-programmable gate arrays (FPGAs), general-purpose graphics processing units (GPGPUs), network middleboxes, and solid-state disks, which promise increased performance, reduced energy consumption, and lower cost profiles, but whose heterogeneity and complexity makes integrating them into the standard cloud Platform as a Service (PaaS) framework a fundamental challenge.

Biography: Alexander L. Wolf serves as Dean of the Baskin School of Engineering and is a Distinguished Professor in the departments of Computer Science and Computer Engineering at the University of California, Santa Cruz (US).

Prof. Wolf’s research interests span the areas of distributed systems, networking, and software engineering. His achievements include seminal work in software architecture, business analytics, and information-centric networks. His more recent projects concern cloud computing, data-center networking, and service-based systems hosted on MANETs.

Prof. Wolf is a Fellow of the ACM, a Fellow of the IEEE, a Chartered Fellow of the British Computer Society (BCS), holder of a Royal Society-Wolfson Research Merit Award, two-time recipient of an ACM SIGSOFT Research Impact Award ([1],[2]), recipient of both the ACM SIGSOFT Outstanding Research Award and Distinguished Service Award, and recipient of an Alumni Award for Outstanding Achievement in Research from the Department of Computer Science at the University of Massachusetts at Amherst.

A Random Walk of Network Science Research: Sub-modularity, Large Graphs Computation and File System Support

John C.S. Lui

Professor, The Chinese University of Hong Kong (CUHK)

Abstract: In this talk, I will provide some motivation of some network science research problems, in particular, I will talk about how one can combine theory of sub-modularity and probabilistic counting data structures to information discovery and computation on large graphs.  I will also discuss how one should re-design the file system support so as to provide a more efficient computation on network science problems.  

Biography:John C.S. Lui is currently the Choh-Ming Li Chair Professor in the Department of Computer Science & Engineering (CSE) at The Chinese University of Hong Kong (CUHK). He received his Ph.D. in Computer Science from UCLA. His current research interests are in network sciences, machine learning, network/system security, network economics, large scale distributed systems and performance evaluation theory. John is currently the senior editor in the IEEE/ACM Transactions on Networking, and has been serving in the editorial board of ACM Transactions on Modeling and Performance Evaluation of Computing Systems, IEEE Transactions on Network Science & Engineering, IEEE Transactions on Mobile Computing, IEEE Transactions on Computers, IEEE Transactions on Parallel and Distributed Systems, Journal of Performance Evaluation. John served as the chairman of the CSE Department from 2005-2011. He received various departmental teaching awards and the CUHK Vice-Chancellor’s Exemplary Teaching Award. John also received the CUHK Faculty of Engineering Research Excellence Award (2011-2012). John is a co-recipient of the best paper award in the IFIP WG 7.3 Performance 2005, IEEE/IFIP NOMS 2006, SIMPLEX 2013, and ACM RecSys 2017. He is an elected member of the IFIP WG 7.3, Fellow of ACM, Fellow of IEEE, Senior Research Fellow of the Croucher Foundation and was the past chair of the ACM SIGMETRICS (2011-2015). His personal interests include films and general reading.


Motion Tracking and Its Applications

Lili Qiu

Professor, University of Texas, Austin

Abstract: Video games, Virtual Reality (VR), Augmented Reality (AR), and Smart appliances (e.g., smart TVs and drones) all call for a new way for users to interact and control them. Motivated by this observation, we have developed a series of novel motion tracking technologies using acoustic signals. A unique feature of our approach is that it can achieve mm-level tracking accuracy on smartphones without special hardware. We further develop a few interesting applications on top of our motion tracking technology. 

Biography: Lili Qiu is a Professor at Computer Science Dept. in UT Austin. She got M.S. and PhD in Computer Science from Cornell University in 1999 and 2001, respectively. After graduation, she spent 2001-2004 as a researcher at System & Networking Group in Microsoft Research Redmond. She joined UT Austin in 2005, and has founded a vibrant research group working on Internet and wireless networks at UT. She has published 100+ papers and 22 issued patents. She is named IEEE Fellow and ACM Distinguished Scientist, and also a recipient of NSF career award and Google Faculty Award.

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