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Introduction to United Devices

Introduction to United Devices. 10 July06. Company. History Founded in 1999, headquarters in Austin, Texas with offices in New Jersey, Ohio, Houston, Chicago, London, Paris, Pune – India 5th generation today - 1st generation technology delivered in late 2000

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Introduction to United Devices

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  1. Introduction to United Devices 10July06 UD CONFIDENTIAL

  2. Company History • Founded in 1999, headquarters in Austin, Texas with offices in New Jersey, Ohio, Houston, Chicago, London, Paris, Pune – India • 5th generation today - 1st generation technology delivered in late 2000 • Focused on large enterprise customers • 7 of the Top 10 pharmaceuticals worldwide • Fortune 100 Manufacturing and Telecommunications • Key Government Agencies • August 5, 2005 – UD acquires GridXpert Meta-Scheduling technology; Moves European HQ to Paris What we do • Our PC-Grid and DRM solutions are implemented across a wide variety of industries and applications • Provide Capacity Management solution to measure & monitor utilization of your resources. • Meta-Scheduling across industry legacy DRM solutions in a heterogeneous environment UD CONFIDENTIAL

  3. Manufacturing Government Education Other • Crash simulation • Assembly interaction • Product Design -Materials modeling -Decryption -Bio-terrorism • -Telecom • Oil & Gas • Philanthropic grids Customer Successes • Providing Grid Solutions since 1999 • 100+ customers • Numerous Enterprise-wide grid deployments Life Sciences -General research -Application development • Drug discovery • Clinical development • Document rendering • Financial Services • Business Applications UD CONFIDENTIAL

  4. 2005 Transaction Profile UD CONFIDENTIAL

  5. We are repeating history Heterogeneous and massively distributed environment Reduced user collaboration and consistency Ad-hoc IT procedures Independent and peak-based procurement Low utilization of resources Minimal resource sharing across user groups Skyrocketing TCO 1,400,000 1,200,000 1,000,000 800,000 Units Sold 600,000 400,000 200,000 0 2003 2004 2005 2006 2007 2008 Problem HPC Evolution 1980s 1990s 2000s Supercomputer Mini-Supercomputer Multi-Processor Servers Proprietary Clusters Commodity Clusters Source: IDC 2005 UD CONFIDENTIAL

  6. Dept A Dept B Project A Project B Dept C Dept D Project C Project D Islands of HPC HPC instance A HPC instance B • Departmental usage promotes independent HPC solutions • A separate installation required to integrate these instances • Addition of more nodes requires manual installation • Fast depreciating and expensive resources are mostly underutilized • Sub-optimal allocation of jobs and application to resources • Relies on a variety of OS services being available HPC instance C HPC instance D UD CONFIDENTIAL

  7. Dept A Dept B Project A Project B Dept C Dept D Project C Project D The HPC Grid Computing Model • 10x reduction in cost – millions of dollars in savings • Nearly 100% resource utilization • Enterprise-wide use for appropriate applications • Preserve departmental control of policies and access controls • Single virtual system view for application developers, administrators, users • Asset appreciates over time – Moore’s Law UD CONFIDENTIAL

  8. Fundamental Capabilities from UD Product: • Security to pass the most stringent audits • Scalability across heterogeneity • Flexible application framework • Dynamic, policy based provisioning • ROI centric software and business design decisions Methodology: • UD Services that align with grid adoption curve • Incremental wins with demonstrable ROI • Balances departmental autonomy and centralized control • HPC Collaboration Experience: • Deploying and operating the world’s largest grids • Distributed computing domain expertise UD CONFIDENTIAL

  9. Where UD Grids Help Today - Industry Applications • Manufacturing • Finite element analysis • Computational fluid dynamics • Crash test simulations • Inventory management • Computer-Aided Design • Verification simulation • Package Design • Synthesis • FPGA design • Multimedia • Library encoding • Graphics rendering • Image compression • Defense & Security • Decryption • Language Translation • Battle simulation • Intelligence gathering • Image analysis • Pattern recognition • Network warfare • Vulnerability Analysis • Steganography • Data Analysis • ETL • Statistics • ERP • Fraud Detection Life Sciences • Proteomics • Genomics • High-Throughput Screening • Clinical Trials • Bio-Medical Engineering • Data Mining Geosciences • Reservoir Modeling • Seismic processing Financial Services • Risk Analysis • Valuation • Pricing Derivatives • Commodity Pricing UD CONFIDENTIAL

  10. VC VC VC LSF LSF LSF LSF LSF LSF LSF LSF LSF LSF LSF LSF LSF LSF SGE LSF PBS LL Condor PC Grid CS Firewall HPC Management Solutions Job Setup and Submission Portal Workflow Scheduling API Insight Data Warehouse HPC Synergy (Meta Scheduling) Management Layer Optimizer Overflow Balancing Licensing HPC Insight Capacity Utilization Forecasting Chargeback Clusters Dedicated Nodes PC Grids Non-dedicated Overflow Utility Infrastructure Layer Other Non-dedicated Nodes UD CONFIDENTIAL

  11. Open Source LSF LSF LSF LSF LSF LSF LSF LSF LSF LSF LSF LSF LSF LSF SGE LSF PBS LL Condor CS PC Grid Meta Scheduling Solution – HPC Synergy • Multi-domain meta-scheduler • Job & Application Abstraction Layer • Job Workflow Model • Collaborative Data Management • License Management HPC Synergy (Meta Scheduling) Optimizer Overflow Balancing Licensing Free Distribution UD CONFIDENTIAL

  12. Today’s Computing Environments Resource n Resource m Location p Which login? Data transfers? Location q How much does it cost? Which location? Which script syntax? User j Which resource? Location v A complex puzzle for business end users User i Location u UD CONFIDENTIAL

  13. Jobs Jobs Application Directory Project Project Application Definition Services Services Services Services Services Application Application Application Platform Data Space Data Space Platform Platform Data Space SNL LANL LLNL Configuring Applications Users Business Application Services Resources UD CONFIDENTIAL

  14. HPC Synergy – Job Submission UD CONFIDENTIAL

  15. HPC Synergy Differentiators • Heterogeneous – Works with all legacy DRM products: LSF, PBS, SGE, Condor, …… • Ease of use - Homogeneous way for end-users to submit jobs and processes on different computing environments • Meta-scheduling - Dynamic distribution of jobs over heterogeneous compute environments and Data transfer & access optimization • Virtualization - Resources, applications, data and associated workflows • Dynamic management - Add/remove platforms/resources depending on availability and load, change queuing, etc. • Monitoring of resources, applications, licenses, and charge back capabilities UD CONFIDENTIAL

  16. VC VC VC LSF LSF LSF LSF LSF LSF LSF LSF LSF LSF LSF LSF SGE LSF PBS LL Condor CS Virtual Cluster Solution • GridMP runs underneath LSF, SGE, or PBS • Non-disruptive to the User – still uses legacy DRM scripts • No UD imposed node limit or OS type restrictions • No UD form factor restrictions (servers, workstations, clusters, PC’s) • Access to unlimited capacity – anywhere in the enterprise Open Source Free Distribution DW Other Non-dedicated Nodes UD CONFIDENTIAL

  17. No Impact to Current User Processes • Option to use existing job submission layer or United Devices DRM • Access to extensive operational data and analytics Job Submitted • Virtual Cluster Speeds Processing and Throughput • Existing dedicated and non-dedicated nodes employed to accelerate processing and increase throughput • Reduced purchasing of new nodes Application Processing • Drill Down into Operational Analytics • Data from grid- and non-grid enabled computing nodes aggregated for unified reporting Utilize Processing Analytics Virtual Cluster Overview Ethernet • Head Node • Job Scheduler • Cluster Mgmt • United Devices Resource Manager and DRM Bridge Non-Dedicated Nodes Interconnect Dedicated Nodes Real-time and Historical Analytics UD CONFIDENTIAL

  18. HPC Insight Open Source Forecasting Chargeback Capacity Utilization LSF LSF LSF LSF LSF LSF LSF LSF LSF LSF LSF LSF LSF LSF SGE LSF PBS LL Condor PC Grid CS Capacity Management Solution HPC Insight • Aggregated capacity & utilization from disparate HPC resources • Unobtrusive access scaling to fully managed • Can export data to other reporting utilities • Integrates w/ HPC Synergy to optimize application/resource bindings • Stand-alone utility or full integration / feedback loop to Synergy HPC Synergy (Meta Scheduling) Optimizer Overflow Balancing Licensing Free Distribution UD CONFIDENTIAL

  19. HPC Insight Users Users Users Applications Applications Applications HPC Analytics Solution Professional Services Capacity Optimization Plan - Inventory - Capacity - Utilization • VP of R&D IT • VP of HPC Strategy • Finance Heterogeneous HPC Environments • HPC Insight product and professional services • Step 1: Measure what you have • Step 2: Understand/Interpret infrastructure and usage information • Step 3: Create a plan for capacity optimization UD CONFIDENTIAL

  20. Collect Data • Aggregate • Transform • Normalize • Summarize • Report Automated Actions HPC Insight Data Collected • Capacity/Utilization • Users • Applications • Jobs • Clusters and Grids • Compute Nodes Data Warehouse Adapter Adapter Adapter Users Applications Users Applications Users Applications • SunSGE • Platform LSF • Altair PBS Pro • Altair Open PBS • Condor • UD Grid MP Legacy Grid Products Native Artifacts Native Artifacts Native Artifacts How HPC Insight Works HPC Insight Grid MP A Grid MP B Other UD CONFIDENTIAL

  21. HPC Insight – Capacity Summary UD CONFIDENTIAL

  22. Drill Down to Detail Reports UD CONFIDENTIAL

  23. Utilization Summary UD CONFIDENTIAL

  24. Application Utilization UD CONFIDENTIAL

  25. Share Data With Other Tools UD CONFIDENTIAL

  26. MP Insight Users Users Applications Applications Workstations Servers Clusters MP Insight A capacity analysis and reporting product providing a detailed view of Grid MP utilization activity Users • - Grid Performance • Utilization Details • - Capacity Planning • - IT Managers • System Administrators • Application Developers Grid MP-Managed Enterprise Grid Environment • Identify Capacity and Utilization Trends • Inform Grid Performance and Workload Optimization • Provide Highly Detailed Job Accounting and Auditing UD CONFIDENTIAL

  27. Accounting • Detailed Grid Usage Chargeback Reports • Track Job Execution Details • Resource Utilization Detail for Compliance Audits • Capture where jobs ran to document compliant machine usage UD CONFIDENTIAL

  28. Performance and Workload Optimization • Review Grid Workload Over Any Time Period • By Application • By User • By Resources • Review Performance Metrics • By Application, Job, Device Group UD CONFIDENTIAL

  29. Drive Grid Utilization • Review Capacity Reports with IT Managers and Prospective Users • Review Utilization Reports with IT Managers and User Prospects UD CONFIDENTIAL

  30. Capacity - Summary UD CONFIDENTIAL

  31. United Devices PartnershipA Strategic Contribution to your Success • Most practical method of providing a centralized HPC service • Heterogeneous philosophy is unique and an absolute requirement • Unprecedented level of visibility and control over the HPC environment • Guaranteed certainty that the optimal set of resources are applied to each request – every time • Proven methodology to incrementally move towards centralized HPC management while retaining end-user autonomy UD CONFIDENTIAL

  32. Testimonials “If you look at dedicated clusters versus a more flexible [grid] environment where you can take advantage of both new acquisitions and existing systems through a single tool, it’s just a better way to invest your money.” – Jeff Mathers, Director of Research Innovation at Johnson & Johnson PRD, where they saved US$1 million in first year of production “We invested roughly $400K in grid software and figure we saved at least $2 million” – Manuel Peitsch, Novartis “It will help us avoid other investments in high-performance computing data servers.” Steffen Neumann, Project Manager for Consulting and Partnerships DaimlerChrysler Research “The Grid MP platform keeps track of all the data related to our job runs – where the job was executed, what type of machine, how long it took. So not only does the grid save us time, but in automating this function it allows us to define a validated process for job execution. That goes a long way toward achieving FDA compliance.” Mark Sale, Global Director of Research Modeling and Simulation - GlaxoSmithKline “[Grid MP] allows us to simulate very high-speed electronics, without investing in expensive new hardware. Because the performance is faster with the grid, we are able to produce even higher quality results for our clients while passing on the cost savings this speed of production allows." Brian Von Herzen, President - Rapid Prototypes “We're running between 8000 and 10,000 runs a day – an amount that was impossible before, without using our supercomputers.” Dr. David Moffet, Associate VP of Research Computing Purdue University UD CONFIDENTIAL

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