IBM Deep Computing for Education Indusrty


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Presentation by Mr.Subram Natarajan Executive – Deep Computing IBM India/SA on IBM Technical Computing for Smarter Planet

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IBM Deep Computing for Education Indusrty

  1. 1. Subram NatarajanExecutive – Deep Computing IBM India/ Technical Computing for Smarter Planet © 2012 IBM Corporation
  2. 2. IBM Deep ComputingThe Technical Computing Mission IBM enables customers to advance R&D innovation and gain competitive advantage by offering a broad portfolio of solutions and a collaborative relationship to ensure success 2 © 2012 IBM Corporation
  3. 3. IBM Deep ComputingWhy Technical Computing - because the market demands it Critical Element of Smarter Planet Agenda – Cloud Computing – Big Data Deep Computing is an Important Business for Enterprises Very Critical Now - Increasingly Critical in the Future Enables innovation and sustained competitive advantage Embrace and extend heterogeneous computing environments Helps develop innovative solutions around Hybrid computing, Energy Efficient computing Lower lifecycle costs 3 © 2012 IBM Corporation
  4. 4. IBM Deep ComputingIBM HPC in History SSEC NORC Stretch 1946 701 1954 “Giant Brain” Fortran 1961 1957 360-95 1953 Time Magazine 1968 19553090 VF 1986 Blue Gene Medal of Watson 2005 Jeopardy! SP Deep Blue Chess RoadRunner Technology 1997 2008 2011 1993 2008 Olympics 1996 RISC 4 1987 © 2012 IBM Corporation
  5. 5. IBM Deep Computing The trends and the trendsetters6 © 2012 IBM Corporation
  6. 6. IBM Deep Computing Growth of the Largest Computers by year 1000x every 10-11 years ExaFlop in 2018-2019! 1 ExaFlop 2018-2019sss 7 © 2012 IBM Corporation
  7. 7. IBM Deep ComputingDo I need Petascale• Of course, without a question..!• The quest has already been started, all the big players are in the boat• The first Exascale system is projected for 2018• Key points to remember… • System-level Reliability, Availability, and Serviceability because of the law of large numbers and Soft Errors • Supplying and paying for the power required to run the machines which can be equivalent to a small town! • Productivity - Finding efficient ways to administer and program machines that may need to support MILLIONS of simultaneous processes!8 © 2012 IBM Corporation
  8. 8. IBM Deep ComputingExaScale Challenges• Power – Using Current #1 on Green500 we will need 2 GW• byte/FLOP interconnect -> $1B to $4B• Chip I/O 5000 pins/chip needed• Data Intensive = 500 Gb/s input networks• New 3D hierarchical memory system needed• Storage = 30 days to backup system• RAS – 10 MTBF /yr on node -> 5 mins to failure• Architecture that applications can scale9 © 2012 IBM Corporation
  9. 9. IBM Deep Computing Roadmap 2012 2013-2014 2016-2020 BG/P BG/QExtreme Scaling EXA- Scale Special Use P6-575 POWER7+ POWER7+ POWER8High-End P7-775 POWER9 P7 Blades P7 755 P7 755 QDR SandyBridgeModular IvyBridge HaswellScale Out iDataPlex © 2012 IBM Corporation
  10. 10. IBM Deep ComputingIncredible Performance Improvements © 2012 IBM Corporation
  11. 11. IBM Deep Computing Moore’s law and DC Performance Delivery © 2012 IBM Corporation
  12. 12. IBM Deep ComputingBroad portfolio of superior products and technology  POWER Systems  Intelligent Cluster  Blue Gene  Storage  iDataPlex  Software 13 © 2012 IBM Corporation
  13. 13. IBM Deep ComputingCapabilities in High Performance Computing Core Domain Skills Technical Support Benchmark Solutions Technical Whitepapers and Redbooks HPC Technical and Sales Specialists Product Expertise Performance Engineering & Optimizations Worldwide network Development and Research14 14 © 2012 IBM Corporation
  14. 14. IBM Deep Computing Power Systems Redefining benchmarks by which performance is measured15 © 2012 IBM Corporation
  15. 15. IBM Deep Computing POWER8 POWER7 45 nm POWER6 65 nm POWER5 130 nm POWER4 180 nm  Dual Core  Dual Core  Multi Core  High Frequencies  Enhanced Scaling  On-Chip eDRAM Dual Core  Virtualization +  SMT  Power Optimized Cores Chip Multi Processing  Memory Subsystem +  Distributed Switch +  Mem Subsystem ++ Distributed Switch  Altivec  Design Phase  Core Parallelism +  SMT++ Shared L2  Instruction Retry  Reliability +  FP Performance + Dynamic LPARs (32)  Dyn Energy Mgmt  VSM & VSX (AltiVec)  Memory bandwidth +  SMT +  Protection Keys+  Virtualization  Protection Keys 2001 2004 2007 2010 16 © 2012 IBM Corporation
  16. 16. IBM Deep Computing IBM Power 755 4-socket server 8-core POWER7 processor modules  32-core 3.3GHz configuration 128GB - 256GB of Memory Optional 2 Port 12X DDR InfiniBand Adapter Energy Star-qualified17 © 2012 IBM Corporation
  17. 17. IBM Deep Computing P7 HPC System Hardware – Node Front View PCIe PCIe L-Link Optical Interface D-Link Optical Interface Interconnectb Interconnect Connects 4 Nodes to form Super Node Connects to other Super Nodes PCIe Hub Interconnect Module (8x) D-Link Optical Interface Memory Connects to other Super Nodes DIMM’s (64x) Memory DIMM’s (64x) D-Link Optical Fiber P7 QCM (8x)WaterConnection 360VDC Input Connector18 © 2012 IBM Corporation
  18. 18. IBM Deep Computing System Packaging Front View   BPA 200 to 480Vac lator Bulk Power Regulator  380 to 520Vdc Bulk Power Regu ller & HUB BPCA-B ro Bulk Power Cont ution  Redundant Power rib Bulk Power Dist lator Bulk Power Regulator  Direct Site Power Feed Bulk Power Regu ller & HUB BPCA-A ro Bulk Power Cont ution  PDU Elimination rib Data Center In a Rack Bulk Power Dist re Compute Disk Enclosu  Storage Unit Storage  4U - 0-6 / Rack CEC Switch  Up To 384 SFF DASD / Unit 100% Cooling CEC  239kg (~526lbs) SuperNode  File System PDU Eliminated CEC C EC Input: C EC 8 Water Lines  CECs 4 Power Cords C EC SuperNode  2U C EC  2-12 CECs/Rack 153.5TB Storage CEC  256 Cores @ 3.8 – 4.0 GHz 192 PCI-e 16x / 12 PCI-e 8x  Per CEC C EC  128 SN DIMM Slots / CEC C EC  8,16, (32) GB DIMMs SuperNode  17 PCI-e Slots C EC  Imbedded Switch C EC  Redundant DCA  159kg (~350lbs) Water  NW Fabric g WCU Conditionin WCU Units  Up to:3072 cores, 24.6TB WCU WCU 19 © 2012 IBM Corporation
  19. 19. IBM Deep Computing Blue Gene Expanding the limits of breakthrough science20 © 2012 IBM Corporation
  20. 20. IBM Deep Computing What is Blue Gene used for? Improve understanding – significantly larger scale, more complex and higher resolution models; new science applications Multiscale and multiphysics – From atoms to mega-structures; coupled applications Shorter time to solution – reducing compute time from months to minutes Materials Science Geophysical Data Processing Life Sciences: Sequencing Life Sciences: In-Silico Molecular Dynamics Upstream Petroleum Trials, Drug Discovery Environment and Biological Modeling Financial Modeling Climate Modeling Computational Fluid Dynamics Brain Science Streaming Data Analysis21 © 2012 IBM Corporation
  21. 21. IBM Deep Computing 4. Node Card: Blue Gene/Q 3. Compute card: One chip module, 32 Compute Cards, Optical Modules, Link Chips; 5D 16 GB DDR3 Memory, Torus Heat Spreader for H2O Cooling 2. Single Chip Module1. Chip:16+2 P cores 5b. IO drawer: 7. System: 8 IO cards w/16 GB 96 racks, 20PF/s 8 PCIe Gen2 x8 slots 3D I/O torus 5a. Midplane: 16 Node Cards •Sustained single node perf: 10x P, 20x L • MF/Watt: (6x) P, (10x) L (~2GF/W, Green 500 criteria) • Software and hardware support for programming models for exploitation of node hardware concurrency 6. Rack: 2 Midplanes © 2012 IBM Corporation
  22. 22. IBM Deep ComputingSystem Power Efficiency (Green500 06/2011)At $.10/kWh => 1MW savings in power saves $1M/year. TCO saving is much more. 2.5 Low power is key to scaling to large systems 2.097 Linpack GF/Watt 2 1.680 1.5 1.376 1 0.852 0.825 0.635 0.484 0.44 0.5 0.370 0.250 0 POWER7 BG/P RR Cray XT5 TianHe- Fujitsu K Titech Nagasaki BG/QDD1 BGQDD2 2011 2007 2008 2009 1A 2010 2010 2010 2011 2010 2011 Source: © 2012 IBM Corporation
  23. 23. IBM Deep Computing Intelligent Cluster System x iDataPlex Customize, optimize and right-size your HPC operations24 © 2012 IBM Corporation
  24. 24. IBM Deep ComputingiDataPlex Cluster Solutions by Industry Segments Mechanical/ Electric Design Derivative Analysis Drug Process Discovery Collaborative Actuarial Simulation Research Seismic Analysis Analysis Bandwidth Asset Liability Protein Consumption Finite Element Folding Numerical Management Analysis Weather Digital Rendering Forecasting Reservoir Portfolio Risk Analysis Analysis Failure Medical Analysis Imaging Gaming High Energy Statistical Physics Analysis Energy Finance Mfg Life Sciences Media Public / Gov’t Clusters are deployed across a broad set of industries, to run a broad set of technical applications. © 2012 IBM Corporation
  25. 25. IBM Deep Computing iDataPlex – Designed for Data Center FlexibilityBroad portfolio of customizable components that adjust to your computing needs Rack Management Appliance 2U Chassis iDataPlex Rear Door Heat Server Tray Exchanger Dual IOTray Storage Tray Switches Storage Drives & Network (front) Options PDUs (rear) 3U Chassis © 2012 IBM Corporation
  26. 26. IBM Deep Computing iDataPlex Rear Door Heat ExchangerA new and more efficient way to cool the Data Center • Increase data center density by eliminating hot/cold aisles • Eliminate rack heat exhaust • Same dimensions as standard iDataPlex rear door 4” deep • Liquid cooling at the rack is 75%-95% more efficient than air cooling by a CRAC • No electrical or moving parts • No condensation • Chilled water Provides Up to 115% Heat Extraction, and can even cool the room! © 2012 IBM Corporation
  27. 27. IBM Deep Computing Deep Computing Software The backbone of high performance computing28 © 2012 IBM Corporation
  28. 28. IBM Deep ComputingA broad collection of software for complete HPC deployment  General Parallel File System  eXtreme Cloud Administration Toolkit (xCAT)  Platform Computing Software (LSF, Symphony)  Engineering and Scientific libraries  Parallel Environment  XL C/C++ and Fortran Compilers 29 © 2012 IBM Corporation
  29. 29. IBM Deep ComputingGeneral Parallel File System IBM General Parallel File A highly available cluster architecture. System (GPFS) is a scalable high- performance file Concurrent shared disk access to a management single global namespace. infrastructure for AIX®, Linux® and Capabilities for high performance Windows systems. parallel workloads.30 © 2012 IBM Corporation
  30. 30. IBM Deep Computing Platform Computing Offerings Technical Computing Scalable, comprehensive cluster and -High Performance Platform LSF grid workload and resource Computing Family management suite for heterogeneous environments Simplified, integrated, purpose-built Platform HPC HPC management software bundled with systems Portal, Workflow, License Mgmt, MPI, Reporting, Analytics, Multi-Cluster, Cluster Mgmt, Harvesting, Adaptive High-throughput, low-latency compute and data intensive Analytics Platform analytics applications Infrastructure Symphony • Highest performance & utilization Family • Complex Computations (i.e., risk) • Big Data Analytics via MapReduce • Extract Transform Load (ETL) © 2012 IBM Corporation31
  31. 31. IBM Deep ComputingBenefits to Educational Institutions  Centralized facility to improve the learning capability to Students and researchers alike  Elevates capabilities to offer advanced research capabilities such as IITs/IISc etc  Benefits extended to several departments – natural and applied sciences and engineering  Future expansion by protecting investment © 2012 IBM Corporation
  32. 32. IBM Deep ComputingWhich Departments Benefit from the setup? Natural Sciences Flexible University HPC Engineering Relations Building Block Computer Sciences © 2012 IBM Corporation
  33. 33. IBM Deep ComputingWhich Departments Benefit from the setup? Collaboration Use Large SMP Programs •Academic Initiative Natural •Chemistry •Content creation & delivery Sciences •Biology training •Weather & Atmospheric Sciences Flexible University HPC Engineering Relations Building BlockComputer Use Clustered Computers•Computer Sciences •Civil & Structural engineering•Computer Engineering (FEA, Structures)•Information Technology Computer •Mechanical (CAD, CAE)•Topics such as Parallel Programming, MPI, Sciences •Nanotechnology (Material andGrid, Cluster Physical Sciences) © 2012 IBM Corporation
  34. 34. IBM Deep Computing Self Service Portal HPC Cloud for Cloud Management Suite Admin: Configure, End-Users: VM Management Manage, Monitor, Requests, Reservations, Run Report, Virtual Servers, workloads, Event Virtual Image Capture, Notification Start, Stop & Deploy, Events & Alerts Machine Requests Image Capture & Reuse Usage Reports User Directory & Security Policy Cloud Events and Alerts Chargeback & Audit Services Energy Monitoring & Management Services Workload Submission and Monitoring System Configuration & Monitoring On-demand Provisioning LoadLeveler xCAT Energy LDAP User Directory Image catalog Optimization HPC Cloud 1. Node config & mgt Database Job Placement 2. VM / Bare-metal deployment and Execution on Linux GPFS Storage mgt Windows HPC Enterprise Linux Network Switch KVM KVM Storage Servers, Tape Disks Storage © 2012 IBM Corporation
  35. 35. IBM Deep ComputingIBM HPC Management Cloud Suite is a key component of theIBM Engineering Cloud LL Web Engineering Cloud EoD (2D Extensions EDA interface)Web Browser &/or Auto submitExceed on Demand Self Service Web Portal Toolset 2D/3D Product Information and Reuse Collaboration Asset Management Enterprise BPM and Integration Design Flow Analytics Optimization/Modeling Cloud Services VALUE ADD SW and Systems Engg CORE Engineering Cloud LoadLeveler Database xCAT IBM HPC Management Suite for Cloud Management and Monitoring Server; License Servers GPFS KVM Xen VMWare Bare Metal SONAS iDataPlex GPFS Storage Systems Servers © 2012 IBM Corporation
  36. 36. IBM Deep Computing IBM University mission: Build relationships of mutual value for fueling the technical talent pipeline, innovation, and growth ● Nurturing young minds to Build a strong pipeline of 21st Century skills ● Taking Gen-next Technology Leadership to Campus ● Collaborate on innovative research with the greatest minds in academia ● Recruit the best and brightest students to bring Innovation at work.Mission: Creating mutual value with the academic community 44 © 2012 IBM Corporation
  37. 37. IBM India – State of Art Offerings to AcademiaUR Deep Computing State of art Collab  Smarter Planet based Projects  Technology Webinars at Platform  Inspires Students to adopt Gen-Next your desktop Caters from Universities Skills  DE & Senior IBMers to Schools  ~200+ Abstracts,350+ students, 50 engaging live with students A program for every colleges participating in 10 smarter  8100+ students , 82+ student and Faculty planet themes with 10 technology colleges reached through areas of ISL IBM Web. 67 sessions Contest IBM IBM Joint development of Collaboration Technology  Deeper Research Platform Webinars Collaborations & Joint Courseware A IP IBMer as Adjunct Progressive  IIT B/IITD/COeP – Cloud Faculty/ Board of Curriculum & approach for SUR & Faculty Faculty Collaboratory Studies Enablement Building Awards  YCMOU – ICT enabled Case Studies for Lab Deep Mass Communication work  IIT G- Improved Global Relations Centre for accessibility Remote Advanced Mentoring Studies  PSG Tech- Public Posters, Seminars & Health Research Grade Projects Diversity Joint mentoring by IBM Focus SME & Faculty  Academia in IT Development Prime Driver : Asset  Promotion of Technical Education Work Generation as Engineers Week : 2000+  Faculty Residency, Student 200+ projects , 15 assets Students Internship created , 1200+ students ,  Grace Hopper Sponsorship  Product Features and market 100 + Colleges participated acceptability 45  One to One Career Mentorship for © 2012 IBM Corporation Web contest winners
  38. 38. IBM Deep Computing Some Achievements of 2011Zinnov Award received for “Ecosystem Enablement- University”Webinar Series: IBM India has become a trendsetter 8100 participants across India, 55 colleges (all IITs participating), 70 sessions already delivered. High impact created due to IBM Fellows and DE s webinar Series. (Average attendance 120/ session)Global Remote Mentoring : 95 projects, 1000 top students, 7 IITs, IRL and global mentors participating, IBM India mentored a Nigerian student. Excellent progress : students and faculty feedback is very encouraging. Creation of valuable Assets in terms of publications, disclosures and assets have won competitions at the national level.IBM India UR facilitated many research awards and initiated collaborative projects with Indian academia.IBM India UR initiating academic activity in the SA region.46 © 2012 IBM Corporation
  39. 39. IBM Deep Computing Thank you !!!47 © 2012 IBM Corporation