3rd International Workshop on Innovating the Network for Data-Intensive Science
INDIS16, the Third Workshop on Innovating the Network for Data-Intensive Science, brings together the network researchers and innovators to present challenges and novel ideas that stretch SCinet and network research beyond the limits of today's technology. This workshop invites papers that propose new and novel techniques regarding capacity and functionality of networks, its control and its architecture to be demonstrated at current and future supercomputing conferences. It will be held during SC16, the International Conference on High Performance Computing, Networking, Analysis, and Storage (http://sc16.supercomputing.org) November 13-16 in Salt Lake City, Utah.
Networks for data-intensive science have more extreme requirements than general-purpose networks. These requirements closely impact the design of processor interconnects in supercomputers/cluster computers, but they also impact campus networks, regional networks and national backbone networks. The ability to move large datasets in and out of supercomputing centers are an an integral and essential part of the data driven Supercomputing ecosystem. Further networks are required to connect research instruments such as photon sources, and large visualization displays. This workshop encourages research papers that address one or more of these needs that are essential in the scientific discovery process. This workshop will also serve as a platform for participants in SCinet to present experimental papers on their latest designs and solutions. Every year SCinet develops and implements the network for the SC conference. SCinet is the high-speed network engine of the SC conference. This network is state of the art, connects many demonstrators of big science data processing infrastructures at the highest line speeds, deploys the newest technologies available, and demonstrates novel functionality. The show floor network connects to many laboratories and universities worldwide using high-bandwidth connections. This workshop brings together SCinet engineers network researchers with to share challenges and potential solutions. Their novel ideas will allow future SCinets to stretch their deployed technologies and further drive new network research. We invite papers that propose new and novel techniques that increase the capacity and functionality of scientific computing and wide-area networks.
This workshop invites papers that propose new and novel techniques regarding capacity and functionality of networks, its control and its architecture to be demonstrated at current and future supercomputing conferences.
Topics of interest include, but are not limited to:
• High-speed network protocols
• Network architectures
• Securing high-speed networks
• High performance data transfer applications and techniques
• Science DMZs and other campus network constructs
• Software-defined networking, OpenFlow and NFV
• Optical networking
• Network monitoring and traffic analytics
• Requirements and issues for network quality of service (QoS)
• HPC interconnects: topologies and protocols for supercomputers and cluster computers
• Storage area networks
• Network management: diagnostics, troubleshooting, fault management, performance monitoring, configuration management
• Multi-domain networking
• Cees de Laat: Professor System and Network Engineering, University of Amsterdam, The Netherlands.
• Brian L. Tierney: Staff Scientist and Group Leader of the ESnet Advanced Network Technologies Group at Lawrence Berkeley National Laboratory.
• Paola Grosso: Assistant professor in the System and Network Engineering (SNE) group at the University of Amsterdam, The Netherlands.
• Malathi Veeraraghavan: Professor, Charles L. Brown Dept. of Electrical and Computer Engineering, and Associate Director, Infrastructure and Services, Data Science Institute, University of Virginia.
• Mehmet Balman: Lawrence Berkeley National Laboratory, USA, NDM committee member.
• Sylvia Kuijpers: SURFnet, The Netherlands, SCinet team-member INDIS and Communication.
• Jason Zurawski, ESnet, Lawrence Berkeley National Laboratory, USA.
• Pavan Balaji, Argonne National Laboratory and Northwestern University, USA.
• Virginia Bedford, US Army Corps of Engineers, USA.
• Surendra Byna, Lawrence Berkeley National Laboratory, USA.
• Jerry Chou, National Tsing Hua University, Taiwan.
• Zhihui Du, Tsinghua University, China.
• Kartik Gopalan, State University of New York at Binghamton, USA.
• Zhiyi Huang, University of Otago, New Zealand.
• Raj Kettimuthu, Argonne National Laboratory and University of Chicago, USA.
• Jinoh Kim, Texas A&M University-Commerce, USA.
• Siva Kulasekaran, Texas Advanced Computing Center, USA.
• Kate Mace, ESnet, USA.
• Manish Parashar, Rutgers University, USA.
• Eric Pouyoul, Energy Sciences Network and Lawrence Berkeley Lab, USA.
• Corby Schmitz, Argonne National Lab/ Loyola University, Chicago, USA.
• Jennifer Schopf, Indiana University, USA.
• Martin Swany, Indiana University, USA.
• Venkat Vishwanath, Argonne National Laboratory, USA.
• Linda Winkler, Arogonne National Lab.
• Wenji Wu, Fermilab, USA.
• Lei Xia, LinkedIn, USA.
• Esma Yildirim, Fatih University, Turkey.
• Yufei Ren, IBM, Watson, USA.
• Matthew J Zekauskas: Senior researcher, Internet2, USA.