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Cloud Computing y Big Data, próxima frontera de la innovación
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Cloud Computing y Big Data, próxima frontera de la innovación

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Jordi Torres, UPC Barcelona Tech. Barcelona Supercomputing Center.

Jordi Torres, UPC Barcelona Tech. Barcelona Supercomputing Center.

Jornada 'El impacto de la Nube y el Big Data en la Ciencia'

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    Cloud Computing y Big Data, próxima frontera de la innovación Cloud Computing y Big Data, próxima frontera de la innovación Presentation Transcript

    • Cloud Computing y Big Data,próxima frontera de la innovaciónCloud Computing and Big Data,the next frontier of innovationJordi Torres, UPC-BSCMadrid, 21 Marzo 2013
    • HOW DID SCIENCE START?
    • Source: Prof. Mateo Valero, BSC-CNS 2010
    • Source: Prof. Mateo Valero, BSC-CNS 2010
    • HOW IS SCIENCE ADVANCING TODAY?
    • Source: Prof. Mateo Valero, BSC-CNS 2010
    • Source: Prof. Mateo Valero, BSC-CNS 2010
    • MATHEMATICAL CALCULATIONS? WHERE?
    • MN3 Cores/chip 8 Chip/node 2Compute Cores/node 16 Nodes 3028 Total cores 48448 Freq. 2,6 Gflops/core 20,8Performance Gflops/node 332,8 Total Tflops 1000,0 GB/core (GB) 2Memory GB/node (GB) 32 Total (TB) 96,89 Latency (μs) 0,7Network Bandwidth (Gb/s) 40Storage (TB) 2000Consumption (KW) 1080
    • FOR SOME SPANISH RESEARCH GROUPS!
    • AND…FOR THE REST OF THE WORLD?
    • GOOD NEWS!Source: http://news.cnet.com/8301-13846_3-57349321-62/amazon-takes-supercomputing-to-the-cloud
    • CLOUD COMPUTING?
    • Source: http://www.wired.com/wiredenterprise/2011/12/nonexistent-supercomputer/all/1
    • Source: http://www.facebook.com/media/ set/?set=a.190842620965185.47008.140375289345252 40 Mw28.000 m2
    • Foto: Google
    • HUGE DATA CENTERSFoto: Google > football pitch x 4
    • Source: http://www.google.com/about/datacenters/gallery/images
    • Source: http://www.google.com/about/datacenters/gallery/images
    • Source: http://www.google.com/about/datacenters/gallery/images
    • Different IT productionFoto: J.T.
    • CLOUD COMPUTING: IT as a serviceOn-demand self-service Pay per use Rapid elasticity Ubiquitous access .... Source: http://www.telegraph.co.uk/technology /reviews/9241719/Power-Ethernet-Sockets-review.html
    • Example of benefits (IaaS):1 computer in a rackfor 120 hours 120 computers in three racks for 1 hour Idea : Tutorial SC2011 - Robert Grossman
    • AND DATA?
    • Source: http://www.docuciencia.es/2009/05/lhc-el-acelerador-de-particulas/“… the LHC produces 1PetaByte of data every second, big data andlack of computing resources were becoming the European Organizationfor Nuclear Research’s biggest IT challenges…” Source: computerweekly.com/news/2240173897/CERN-adopts -OpenStack-private-cloud-to-solve-big-data-challenges
    • 1 Gigabyte (GB) = 1.000.000.000 byte1 Terabyte (TB) = 1.000 Gigabyte (GB)1 Petabyte (PB) = 1.000.000 Gigabyte (GB)1 Exabyte (EB) = 1.000.000.000 Gigabyte (GB)1 Zettabyte (ZB) = 1.000.000.000.000 (GB)
    • Deluge of data created daily Source: Economist , Feb 25th, 2010 http://www.economist.com/node/15579717
    • Big Data?definition?
    • BIG DATA?Big Data is data that exceeds thestoring, processing and managingcapacity of conventional systems.
    • BIG DATA?The reason is that the data is toobig, moves too fast, or doesn’t fitthe structures of our current systems’architectures.
    • BIG DATA?Moreover, to gain value from thisdata, we must change the way toanalyze it.
    • BIG DATA?Big Data is data that exceeds the storing,processing and managing capacity ofconventional systems.The reason is that the data is too big,moves too fast, or doesn’t fit thestructures of our current systems’architectures.Moreover, to gain value from this data, wemust change the way to analyze it.
    • NEW CHALLENGESthat must be addressed urgently, in order to respond to the needs of the advancement of science 1. Storing 2. Managing 3. Processing 4. Analyzing
    • Affordable Storage
    • But scanning disks…assume 100MB/sec
    • But scanning disks…assume 100MB/secmore than 5 hours
    • approach: massive parallelism assume 20.000 disks:scanning 2 TB takes 1 secondSource: http://www.google.com/about/datacenters/gallery/images/_2000/IDI_018.jpg
    • 1 Data processing challengesRethinking data processing is required: MapReduce, Storm, S4,… Source: http://www.google.com/about/datacenters/gallery/images/_2000/IDI_018.jpg
    • 2 Data storage challengesNew Storage technologies are required HHD 100 cheaper than RAM But 1000 times slowerRAM vs HHD Solid- state drive (SSD) Not volatilePresent solutions: Storage Class Memory (SCM)Research:
    • 3 Data management challenges Relational DB can’t support everythingExample: eventual consistencySolution: “NoSQL systems”Research: New management systems Source: gigaom.com/cloud/big-data- and-nosql-march-to-the-enterprise/ 43
    • 4 Obtaining value from data The information is non actionable knowledge- Data prediction using data mining & + machine learning techniquesValue Volume Information Research: The majority of algorithms function well in thousands of+ registers, however at the moment they Knowledge - are impractical for thousands of milions.
    • Cloud Computing and Big Data:the next frontier of science and innovation
    • Thank you for your attentionwww.JordiTorres.org - @JordiTorresBCN www.smartcityexpo.com www.bsc.es/eBusiness Autonomic Systems and e-Business Platforms research line at BSC/UPC
    • Thank you for your attentionwww.JordiTorres.org - @JordiTorresBCN www.smartcityexpo.com www.bsc.es/eBusiness Autonomic Systems and e-Business Platforms research line at BSC/UPC