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INSTITUTE OF COMPUTING TECHNOLOGY

INSTITUTE OF COMPUTING TECHNOLOGY. Computing for the Masses 为人民计算 Zhiwei Xu 徐志伟 Information Science Advisory Committee, NSFC Institute of Computing Technology (ICT) Chinese Academy of Sciences zxu@ict.ac.cn. Contents. Background Goals Problems and Approaches.

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INSTITUTE OF COMPUTING TECHNOLOGY

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  1. INSTITUTE OF COMPUTING TECHNOLOGY Computing for the Masses为人民计算Zhiwei Xu徐志伟Information Science Advisory Committee, NSFCInstitute of Computing Technology (ICT)Chinese Academy of Scienceszxu@ict.ac.cn

  2. Contents • Background • Goals • Problems and Approaches

  3. Demand: China Computer Market Grows Still has big growth space Internet Penetration (2007) China 16% USA 70% World 19% China in 10 years = USA today? 2007 3.38 93.1 210 78 Sources: China NBS, CCID, CNNIC, Goldman Sachs

  4. Supply: China computer industry is weak(Forbes 2000 for year 2007 US$ billion)

  5. Challenges to Academia • C4M supply is seriously lacking • Lag behind demandLag behind industry • Lag behind international peersToo much short-term “mission”

  6. Computing for the Masses (C4M) • Research and applications of computer science for mass adoption • Directly benefit the masses • Billions of people ≠scientific computing or business computing • Including • Parallelism for the masses • Net computing for the masses • Social computing for the masses

  7. Contents Background Goals Mass Adoption  billions of people No dumbing down: Value = Ω(Adoption) Sustainability: Value↑, resource→ Problems and Approaches

  8. Sustainability Value & Resource Energy/operation(2000-2007) Total IT Value μJ Systems Resource consumption Environment impact Circuits pJ Servers electricity bill: $1.9 billion (IDC, 2007 China ) Physics 1960 1970 19801990 2000 2010 2020 2030 2040 Time

  9. 2020 2030 2040 C4M is not dumbing down Value Personalized Expertise Ubiquity Commodity Basic 2010 Adoption (Computer Users in China, Billion) 0.10.2 0.3 0.40.5 0.6 0.8 1.01.2

  10. Value-Augmenting Adoption • PC: example of C4M • Reached more users • More value than mainframe/mini • More innovations with big ideas • Frame buffer • GUI • OO programming • Ethernet Value Personalized Expertise Ubiquity Commodity Basic 2040 2030 2020 2010 Adoption (Computer Users in China, Billion) 0.10.2 0.3 0.40.5 0.6 0.8 1.01.2

  11. What’s different now? • The Net = Three Worlds • Man-Machine Symbiosis  Man-Machine Society

  12. Godson CPULenovo PC/LaptopDawning ServersBlueWhale StorageVega Grid Computing for the Masses Computer users in China:210 million (2007); 800 million (2020) Business Value Utility Devices Business App & Svc Business Infrastructure IT Infrastructure IT Components Servers, NetworksStorages, Data Sensor Networks, CPS

  13. Contents • Background • Goals • Problems and Approaches • A Science of Three Worlds • Architectural Characteristics • Personal Net

  14. A Science of Net Computing • Computation as a unifying theme in a new science of three worlds • Enrich our beautiful algorithmic computing theory • Karp • Computational lens • Hurwicz • Mechanism design • Science 2020

  15. Google-Like Computing 2006 Data ($ billion) Revenue:10.6 Profit: 3 Cost: 7 R&D:1.2 Resource: 2.4 Google Value (Visible)Search, AdWord, Map, Earth, News, Froogle, etc. Google application software and data Sorting, machine learning, graph computing, etc. Google utilities: MapReduce & BigTable Google system softwareGoogle filesystem, resource mngt, fault tolerance, etc. Hosting Environment: LAMP Linux Servers and Other Resources Distributed in Wide Area DatacentersServersData, MetadataCode O=F(I)  Value = F(Resource)

  16. Enrich Algorithmic Computing • Traditional algorithmic computing • Turing machine decision problem • Input, output, a procedure of mechanic steps • Time complexity, space complexity • What are “algorithms” in the tri-world? • What is the “decision problem”? • What is Web computable? • What is Wiki computable? • How to quantify “value” and “resource”? • What is a “step”? What is termination? • What are the complexity metrics?

  17. System Characteristics • C4M Workload Analytics • Time, space, information • Interaction, energy, effort • Basic “Laws” revisited • Moore’s law • Network effect (Metcalf, Brown) • Viral market • Internet principles (E2E, REST) • New Phenomena and Abstractions

  18. Architecture Characterization • Patterson & Hennessey Performance = Program/Time = 1/(#Instructions x CPI x CycleTime) • Need reexamination • Program=C4M workloads • Time=? • Instruction=? • Other important metrics Task/Energy = ? Task/Effort = ?

  19. Architecture Characterization Admin, Knowledge, Naming, Coding, Contribution Distributed Systems Control WWWCloudsPNC environment Virtual hosts Virtual Machines DecentralizedSystems Decentralized Centralized GoogleAmazonTeragrid Salesforce.com many web sites Execution Single Multiple Number of Execution Sites (Datacenters, Machines)

  20. Personal Net (PN) • A PN for each member of the masses • A general-purpose, personal, net computing platform • a dynamic, virtualized set of assets from the Net (cyberinfrastructure, community, physical world) • appearing to be dedicated to a personal owner’s use and control • People share the Net personally

  21. The Net Now • Offering • Traditional network services: email, ftp, BBS, messaging • Consumer web: Amazon, eBay • Business web: salesforce.com • Community Web: Wiki, MySpace, Facebook • Grid services: Nanohub • Platform: Teragrid, Amazon S3 and EC2 (clouds) • Characteristics • Institutional, not personal • Special-purpose solutions, not a general-purpose platform • The Net now is like the Mainframe in 1960’s

  22. Grids Clouds DISC Individuals AccessingDevices The Net A, D O, P C, N, S A, D O, P C, N, S A, D O, P C, N, S A, D O, P C, N, S PersonalGrids …… …… PlatformProviders PG Platform Provider PG Platform Provider ResourceProviders ASP DSP CSP SSP NSP …… ASP Personal Net Computing PocketWeb Assets A: applications D: data O: operating sys. P: policies C: computing N: networking S: storage SP: service provider for resources Resources are “raw” assets (capabilities) Pocket Web: battery life > 2 weeks; assets on demand; the Net in you hand

  23. Characterizing Emergence Dual-objective optimization Fairness Success Rate

  24. Emergencesdo appear Xiao et al, “Incentive-based Scheduling for Market-like Computational Grids”, IEEE Transactions on Parallel and Distributed Systems, 2008 • Workloads (over 1 million jobs simulated) • Synthetic workloads • Real workloads：www.cs.huji.ac.il/labs/parallel/workload/ • Value For consumers: for providers: high job success rate fair revenue and utilization

  25. AppThread App Database OS VMM Thread VMM HW system HW (core) Clash of the Computer and the Network Approaches • Fetching 10-byte data from a blog server: 162 ms,52 context switchesat server side • How much is needed to host 100 million PG’s? • Response time < 0.25 s • Sustained = 5% Peak? TCP/IP Stack Web/Web Service Stacks 4 Application GSML BPEL WSRF WSDL SOAP HTML XML HTTP ? 3 Transport 2 Inter Network 1 Network Access

  26. Summary • CS research lags behind demand • C4M is potentially a transformative opportunity for CS research • C4M means sustainability and value-augmenting mass adoption • C4M research agenda • Establish a science of three worlds • Characterize net computing architectures • Create personal net

  27. Thank you! zxu@ict.ac.cn

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