PDF-Duet: Cloud Scale Load Balancing

with Hardware and Software 1 Hongqiang Harry Liu Guohan Lu Jitu Padhye Lihua Yuan Ming Zhang Rohan Gandhi Y Charlie Hu Load Balancer is Critical For Online Services 2 Server S. Charlie Hu Guohan Lu Jitendra Padhye Lihua Yuan Ming Zhang Microsoft Purdue University Yale University ABSTRACT Load balancing is a foundational function of datacenter infrastruc tures and is critical to the performance of online services hosted i as well as the server?. Nikhil Handigol. Stanford University. Joint work with Nick . McKeown. and . Ramesh. . Johari. Datacenter. Wide-area. Enterprise. Can’t choose path :’(. LOAD-BALANCER. Client. Haidong. . Xue. Part One: Knowledge in Textbook. Motivation, Models, Concepts, Algorithms. Part Two: Recent Work. Use the Mobile Agent and Include I/O. Duplex Loading Balancing Strategy. Stability Analysis Based. Sig Freund. Outline. Introduction. Distributed vs. Traditional . scheduling. Process Interaction models. Distributed . Systems. Research Studies. Guess about the Future?. Questions. Introduction. Load Sharing. Presented by Paul. Problem. The cloud offers. Near infinite computing capabilities. Near infinite storage. On-demand access to new VMs. Pay-as-you-go model. But how do you build an application to automatically take advantage of those resources?. Tensor Contractions. David . Ozog. *, Jeff R. Hammond. †. , James . Dinan. †. , . Pavan. . Balaji. †. , Sameer . Shende. *, Allen . Malony. * . *University of Oregon . †. Argonne National Laboratory. Rusty Lusk. Mathematics and Computer Science Division. Argonne . National Laboratory. Outline. Introduction. Two abstract programming models. Load balancing and master/slave algorithms. A collaboration on modeling small nuclei. Aran Bergman. (Technion, VMware). Naga Katta, Aditi . Ghag. , . Mukesh. Hira, . Changhoon. Kim, Isaac . Keslassy. , Jennifer Rexford. CLOVE. 1. Data center load balancing today. E. qual-. C. ost . Presented by Paul. Problem. The cloud offers. Near infinite computing capabilities. Near infinite storage. On-demand access to new VMs. Pay-as-you-go model. But how do you build an application to automatically take advantage of those resources?. Sig Freund. Outline. Introduction. Distributed vs. Traditional . scheduling. Process Interaction models. Distributed . Systems. Research Studies. Guess about the Future?. Questions. Introduction. Load Sharing. Vlad. . Nae. , . Radu. . Prodan. , Thomas . Fahringer. Institute of Computer Science. University of Innsbruck. 10/25/2010. MMOG Subscriptions (last 10 years). 1. Introduction. 24 million subscribers. Highlights. Ignacio Reguero . Naredo and Lorena Lobato Pardavila. CHEP 2016. . Octo. ber 10-14 . 2016. 1. CHEP 2016 October 10-14 2016 DNS Load Balancing in the CERN Cloud Highlights. DNS Load Balancing is Cost Effective. Rusty Lusk. Mathematics and Computer Science Division. Argonne . National Laboratory. Outline. Introduction. Two abstract programming models. Load balancing and master/slave algorithms. A collaboration on modeling small nuclei. Gengbin. . Zheng. , Esteban . Meneses. , . Abhinav. . Bhatele. and . Laxmikant. V. Kale. Parallel Programming Lab. University of Illinois at Urbana Champaign. Motivations. Load balancing is key to scalability on very large supercomputers.