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Introduction From 1975 till 2005: Computing Science at CERN - PowerPoint PPT Presentation

Aug 22, 2023 •353 likes •727 views

Introduction From 1975 till 2005: Computing Science at CERN (www.cern.ch) Developing HPC distributed computing solutions for HEP Including EU-DataGrid and EGEE, foundation for the present LHC distributed computing Grid infrastructure

  2. Introduction From 1975 till 2005: Computing Science at CERN (www.cern.ch) • Developing HPC distributed computing solutions for HEP • Including EU-DataGrid and EGEE, foundation for the present LHC distributed computing Grid infrastructure (www.eu- egee.org) • Extending support to other scientific communities in the EU European Research Area context • Among them OGF-Europe and the follow on SIENA project active of Grid and Cloud computing standards • Deploying Cloud Computing for Science and Technology with VENUS-C (www.venus-c.eu)

  3. Microsoft Research Connections Collaborations to pursue scientific breakthroughs Work with the worldwide academic Inspire emerging research community computer and to speed research, research improve education, scientists and foster innovation Accelerate scientific exploration with computing

  4. Microsoft Research Labs External Research Groups Technology Learning Labs Collaborative Institutes and Centers

  5. Barcelona Supercomputing MSRC expertise: programming Centre: computer architecture, language and operating system parallel programming models design & implementation Research at the intersection of computer architecture, language implementation, and systems software Language runtime system Low-power vector processors Transactional memory (TM) – Architecture support to – New vectorization techniques for – Abstraction for scalable shared- accelerate synchronization and cloud computing and mobile memory data structures garbage collection applications – Research on using TM in real – “Dynamic filtering” support for – Fusion of Edge and E2 with vector applications; game servers, GC read/write barriers (ASPLOS techniques recognition-mining-synthesis 10) More on: http://www.bscmsrc.eu/ – Debugging and profiling – H/W abstractions for fast and – Major publications include scalable locking PPoPP 09, MICRO 09, PPoPP

  6. The Microsoft Research-INRIA Joint Centre • • The Centre's objective is to pursue fundamental, long- term research in formal methods, software security, and the application of Computer Science research to the Computational Science. • The Joint Centre benefits from the collaboration of 35 researchers from INRIA and other French academic institutions, 25 post docs and PHD students and 15 researchers from Microsoft Research. • More on: http:// www.msr-inria.inria.fr /

  7. • • • • 7

  8. Focus areas • – Software engineering, reliability, verification – Multicore and multiprocessor systems • Teams collaborate during the design process: – architecture (BSC) – systems (MSR) – software engineering (KU) • Software engineering tools for – novel multicore architectures – novel concurrent programming approaches • Verification tools early in the design process – Not as a late-stage debugging tool only.

  9. Collaborative Research in Computer Vision with MSU Dr. Anton Dr. Pushmeet Kohli, Konushin, MSR Cambridge MSU Dr. Carsten Rother, Dr. Olga Barinova. MSR Cambridge MSU Dr. Victor Lempitsky, Yandex/MSU Undergraduate and PhD students: Mikhail Sindeev Elena Tretiak Sergey Milyaev Roman Shapovalov Tatiana Novikova

  10. 2011 Microsoft Computer Vision Summer School in Russia Facts & figures: • 520+ registrations • 70+ cities • 80 students selected The school offered students a unique opportunity to learn about fundamental and state of the art on Computer Vision from top scientists , including Andrew Blake, Andrew Fitzgibbon, Carsten Rother (Microsoft Research, UK), Andrew Zisserman (University of Oxford, UK).

  11. PhD Scholarship • Goals – Encourage interdisciplinary research – Advance the state of the art – Create a community – Identify potential interns & employees • Open & competitive – Application by research supervisors – Selection ratio 17% – Up to one year to find best possible students • More than funding – Co-supervisions by MSR researchers – Internship – Summer School 7/27/2012 11

  12. MSR Summer Schools • Networking – Other students, MSRC researchers, Cambridge academics • ‘Transferable skills’ – Write paper, give talk, becoming an entrepreneur, applying for funding • Research talks • Poster sessions • Social activity

  13. Experiments Simulations Archives Literature Instruments The Challenge : Enhance our Lives: Enable Discovery . Participate in our own health care. Augment experience Deliver the capability to mine, with deeper understanding . search and analyze this data in near real time. Petabytes Digital information By 2020, more than 1/3rd of all created annually will digital information created grow by a factor of 44 annually will either live in or from 2009 to 2020 pass through the cloud. (Source: EMC-sponsored IDC study)

  14. A Tidal Wave of Scientific Data

  15. Emergence of a Fourth Research Paradigm 2   .     2 a 4 G c        2 a 3 a   Captured by instruments • Generated by simulations • Generated by sensor networks • eScience is the set of tools and technologies to support data federation and collaboration • For analysis and data mining • For data visualization and exploration • For scholarly communication and dissemination ( With thanks to Jim Gray)

  16. Changing Nature of Discovery Complex models • Multidisciplinary interactions • Wide temporal and spatial scales Large multidisciplinary data • Real-time steams • Structured and unstructured Distributed communities • Virtual organizations • Socialization and management http://research.microsoft.com/en-us/collaboration/fourthparadigm/

  17. Machine Translation: The Statistical Revolution Exploit large volumes of existing parallel text • Learn how words, phrases, and structures translate in context •

  18. All Scientific Data Online • Many disciplines overlap and use data from other sciences. Literature • Internet can unify all literature and data • Go from literature to computation to Derived and data back to literature. recombined data • Information at your fingertips – For everyone, everywhere Raw Data • Increase Scientific Information Velocity • Huge increase in Science Productivity ( From Jim Gray’s last talk)

  19. • A model of computation and data storage based on “pay as you go” access to “unlimited” remote data center capabilities • A cloud infrastructure provides a framework to manage scalable, reliable, on-demand access to applications • A cloud is the “invisible” backend to many of our mobile applications • Historical roots in today’s Internet apps and previous DCI computing (Cluster, Grid etc.)

  20. Essentially driven by economies of scale • Approximate costs for a small size center (1K servers) and a larger, 100K server center. Technology Cost in small- Cost in Large Ratio sized Data Data Center Center Network $95 per Mbps/ $13 per Mbps/ 7.1 Month month 5.7 Storage $2.20 per GB/ $0.40 per GB/ Each data center is Month month 11.5 times 7.1 Administration ~140 servers/ >1000 Servers/ the size of a football field Administrator Administrator

  21. Microsoft’s Datacenter Evolution Datacenter Co- Quincy and San Chicago and Dublin Modular Datacenter Location Antonio Generation 3 Generation 4 Generation 1 Generation 2 Facility PAC Deployment Scale Unit IT PAC Server Rack Containers Density Capacity and Deployment Scalability and Time to Market … Sustainability Lower TCO

  22. Windows Azure Platform Availability Northern Europe North Central USA Eastern Asia Western Europe South Central USA Southeast Asia

  23. • Environmental responsibility - Managing energy efficiently - Adaptive systems management • Provisioning 100,000 servers - Hardware: at most one week after delivery - Software: at most a few hours • Resilience during a blackout/disaster - Service rollover for millions of customers • Software and services - End-to-end communication - Security, reliability, performance, reliability

  24. F ocus Client + Cloud for Research Seamless interaction • Cloud is the lens that magnifies the power of desktop • Persist and share data from client in the cloud • Analyze data initially captured in client tools, such as Excel – Analysis as a service (think SQL, Map-Reduce, R/MatLab) – Data visualization generated in the cloud, display on client – Provenance, collaboration, other ‘core’ services…

  25. Give the standard science and engineering desktop tools a seamless extension Use a spreadsheet to invoke genomic analysis tools running on 600 servers Use a simple script to orchestrate data analytics and mining across 10000 MRI Images Pull data from remote instruments for visualization on the desktop

  27. VENUS-C Microsoft Research Cambridge

  28. Three Pillars for Cloud • Legal frameworks • Technical and commercial fundamental elements • Development of the cloud market by supporting pilot projects of cloud deployments Official opening of the Microsoft Cloud & Interoperability Center, March 2011 Neelie Kroes on international standardisation & open specifications “I count here on the further support and commitment of Microsoft and all the other participants.”

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