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Cloud Computing Research at T U Delft (and TU / e )

Cloud Computing Research at T U Delft (and TU / e ). Alexandru Iosup. Parallel and Distributed Systems Group Delft University of Technology The Netherlands. 3TU. =. +. +.

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Cloud Computing Research at T U Delft (and TU / e )

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  1. Cloud Computing Research at TU Delft (and TU/e) Alexandru Iosup Parallel and Distributed Systems GroupDelft University of TechnologyThe Netherlands 3TU. = + + Our team: Undergrad Gargi Prasad, Arnoud Bakker, Nassos Antoniou, Thomas de Ruiter, … Grad Siqi Shen, Nezih Yigitbasi, Ozan Sonmez Staff Henk Sips, Dick Epema, Alexandru Iosup Collaborators Ion Stoica and the Mesos team (UC Berkeley), Thomas Fahringer, Radu Prodan (U. Innsbruck), Nicolae Tapus, Mihaela Balint, Vlad Posea (UPB), Derrick Kondo, Emmanuel Jeannot (INRIA), ... EIT Meeting, Berlin, 24 February 2011

  2. PDS Group: Past Research in Grids • The Koala Grid Scheduler • Co-allocation • Deployed since 2005 • DAS-2,-3,-4 • A Grid Research Toolbox • The Grid Workloads Archive • GrenchMark • DGSim • Performance models • Availability models http://gwa.ewi.tudelft.nl DGSim

  3. A View on Cloud Computing “The path to abundance” On-demand capacity Pay what you use Great for web apps (EIP, web crawl, DB ops, I/O) VS Tropical Cyclone Nargis (NASA, ISSS, 04/29/08) http://www.flickr.com/photos/dimitrisotiropoulos/4204766418/ • “The killer cyclone” • Not so great performance for compute- or data-intensive e-Science apps1 • Performance variability2 1- Iosup et al., Performance Analysis of Cloud Computing Services for Many Tasks Scientific Computing, IEEE TPDS, 2011 (in print) http://www.st.ewi.tudelft.nl/~iosup/cloud-perf10tpds_in-print.pdf 2- Iosup et al., On the Performance Variability of Production Cloud Services, CCGrid 2011, pds.twi.tudelft.nl/reports/2010/PDS-2010-002.pdf Cloud Futures Workshop 2010 – Cloud Computing Support for Massively Social Gaming 3

  4. Cloud Performance Studies • Many-Tasks Scientific Computing • Quantitative definition: J jobs and B bags-of-tasks • Extracted proto-MT users from grid and parallel production environments • Performance Evaluation of Four Commercial Clouds • Amazon EC2, GoGrid, Elastic Hosts, Mosso • Resource acquisition, Single- and Multi-Instance benchmarking • Low compute and networking performance • Clouds vs Other Environments • Order of magnitude better performance needed for clouds • Clouds already good for short-term, deadline-driven scientific computing 1- Iosup et al., Performance Analysis of Cloud Computing Services for Many Tasks Scientific Computing, IEEE TPDS, 2011 (in print) http://www.st.ewi.tudelft.nl/~iosup/cloud-perf10tpds_in-print.pdf 2- Iosup et al., On the Performance Variability of Production Cloud Services, CCGrid 2011, pds.twi.tudelft.nl/reports/2010/PDS-2010-002.pdf

  5. Trace ID Total IO [MB] Rd. [MB] Wr [%] HDFS Wr[MB] CWA-01 10,934 6,805 38% 1,538 CWA-02 75,546 47,539 37% 8,563 The Cloud Workloads Archive • Looking for invariants • Wr [%] ~40% Total IO, but absolute values vary • # Tasks/Job, ratio M:(M+R) Tasks, vary • Understanding workload evolution

  6. More Research on Clouds at TU Delft Scheduling cloud workloads • MapReduce • Scientific applications Cloud-based gaming infrastructure • Massive Gaming is multi-billion business • Driver for cloud resource management research • Driver for distributed systems research • CAMEO: MMOG Analytics • POGGI: Game Content Generation A. Iosup et al., CAMEO: Enabling Social Networks for Massively Multiplayer Online Games through Continuous Analytics and Cloud Computing, ACM NetGames (2010) A. Iosup, POGGI: generating puzzle instances for online games on grid infrastructures. CCPE 23(2): 158-171 (2011)

  7. Take Home Message: 3-TU Research in Clouds • Understanding how real clouds work • Modeling cloud infrastructure (performance, availability) and workloads • Compare clouds with other platforms (grids, parallel production env., p2p,…) • The Cloud Workloads Archive: easy to share cloud workload traces and research associated with them • Complement the Grid Workloads Archive • Scheduling: making clouds work • eScience and gaming applications • MapReduce • Massive Gaming: services on clouds • CAMEO: Massive Game Analytics • Toolkit for Online Social Network analysis • POGGI: game content generation at scale Publications2008: ACM SC2009: ROIA, CCGrid, NetGames, EuroPar (Best Paper Award) 2010: IEEE TPDS, Elsevier CCPE,…2011: ICPE, CCGrid, Book Chapter CAMEO, IEEE TPDS, IJAMC, …  See Pascal van Eck’s presentation

  8. Thank you for your attention! Questions? Suggestions? Observations? More Info: Alexandru IosupA.Iosup@tudelft.nlhttp://www.pds.ewi.tudelft.nl/~iosup/ (or google “iosup”)Parallel and Distributed Systems GroupDelft University of Technology • http://www.pds.ewi.tudelft.nl/publications.php • http://www.st.ewi.tudelft.nl/~iosup/research_cloud.html Do not hesitate to contact me…

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