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1 Grid Computing (2) (Special Topics in Computer Engineering) Veera Muangsin 30 January 2004.

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Presentation on theme: "1 Grid Computing (2) (Special Topics in Computer Engineering) Veera Muangsin 30 January 2004."— Presentation transcript:

1 1 Grid Computing (2) (Special Topics in Computer Engineering) Veera Muangsin 30 January 2004

2 2 Outline High-Performance Computing Grid Computing Grid Applications Grid Architecture –Parallel Computers Architectures –Cluster Architecture –Grid Architecture Grid Middleware Grid Services

3 3 Parallel Computer Architectures

4 4 Parallel Architecture Taxonomy Single Instruction Single Data (SISD ) Multiple Instruction Single Data (MISD) Single Instruction Multiple Data (SIMD) Multiple Instruction Multiple Data (MIMD) –Shared Memory MIMD –Distributed Memory MIMD

5 5 SISD : A Conventional Computer  Speed is limited by the rate at which computer can transfer information internally. Processor Data Input Data Output Instructions Ex: PC, Macintosh, Workstations

6 6 The MISD Architecture  More of an intellectual exercise than a practical configuration. Few built, but commercially not available Data Input Stream Data Output Stream Processor A Processor B Processor C Instruction Stream A Instruction Stream B Instruction Stream C

7 7 SIMD Architecture Ex: CRAY machine vector processing C i <= A i * B i Instruction Stream Processor A Processor B Processor C Data Input stream A Data Input stream B Data Input stream C Data Output stream A Data Output stream B Data Output stream C

8 8 Unlike SISD, MISD, MIMD computer works asynchronously. Shared memory (tightly coupled) MIMD Distributed memory (loosely coupled) MIMD MIMD Architecture Processor A Processor B Processor C Data Input stream A Data Input stream B Data Input stream C Data Output stream A Data Output stream B Data Output stream C Instruction Stream A Instruction Stream B Instruction Stream C

9 9 MEMORYMEMORY BUSBUS Shared Memory MIMD machine Communication between processors via global shared memory Easy to build, conventional OSes of SISD can be easily be ported Limitation : expandability & reliability Ex: dual-processor, quad-processor workstations MEMORYMEMORY BUSBUS Global Memory System Processor A Processor A Processor B Processor B Processor C Processor C MEMORYMEMORY BUSBUS

10 10 MEMORYMEMORY BUSBUS Distributed Memory MIMD lCommunication : IPC on High Speed Network. lUnlike Shared Memory MIMD  easily/ readily expandable  Highly reliable (any CPU failure does not affect the whole system) Processor A Processor A Processor B Processor B Processor C Processor C MEMORYMEMORY BUSBUS MEMORYMEMORY BUSBUS Memory System A Memory System A Memory System B Memory System B Memory System C Memory System C IPC channel IPC channel

11 11 Clusters Distributed Memory MIMD The most common architecture in the TOP500

12 12 Top 2-5 Clusters #2 LANL’s ASCI Q 13.88 TFlops 8192-node cluster HP AlphaServer 1.25 GHz #3 Virginia Tech’s System X 10.28 TFlops 1,100-node cluster, Apple G5

13 13 #4 NCSA’s Tungsten 9.81 TFlops 1,450-node cluster, dual-processor Dell PowerEdge 1750 #5 PNNL’s MPP2 8.63 TFlops 980-node cluster, HP Longs Peak, dual Intel Itanium-2 1.5 GHz

14 14 Zeus and Athena Apollo Our Parallel Computers

15 15 Our Parallel Computers Apollo Cluster 6-node cluster Athlon XP 2000+ processor, 512 MB memory Linux + MPI + PBS (batch scheduler system) + Globus (Grid middleware) Zeus and Athena Two 4-processor Sun Enterprise 420R multiprocessor computers 450 MHz UltraSPARC II processors, 1 GB memory Solaris + Pthread + MPI

16 16 Cluster Architecture

17 17 Cluster Middleware Resides Between OS and Applications and offers in infrastructure for supporting: –Single System Image (SSI) –System Availability (SA) SSI makes collection appear as single machine SA - Check pointing and process migration

18 18 Single System Image Components NFS (Network File System) NIS (Network Information System) NTP (Network Time Protocol) server client

19 19 Programming Environments Threads (Cluster of SMPs) –POSIX Threads –Java Threads Message Passing –MPI –PVM Virtual Shared Memory Batch Scheduling –PBS, Condor, etc.

20 20 Batch Scheduling Process distribution Load balancing Job scheduling PBS, Condor, Sun Grid Engine, IBM Load Leveler, LSF, DQS, …

21 21 Cluster Applications Sequential Parallel / Distributed (Cluster-aware app.) –Grand Challenging applications Weather Forecasting Quantum Chemistry Molecular Biology Modeling Engineering Analysis (CAD/CAM) ………………. –Web servers, data-mining

22 22 Grid Architecture

23 23 What is Grid ? An infrastructure that dynamically couples –Computers (PCs, workstations, clusters, traditional supercomputers, and even laptops, notebooks, mobile computers, PDA, and so on) –Software (e.g., renting special purpose applications on demand) –Databases (e.g., transparent access to human genome database) –Special Instruments (e.g., radio) –People across the local/wide-area networks (enterprise, organisations, or Internet) and presents them as a unified resource or problem solving environment.

24 24 Grid Infrastructure

25 25 TeraGrid

26 26 Grid Applications Old and new applications getting Grid-enabled via coupling of computers, databases, instruments, people, etc: –(distributed) Supercomputing –Collaborative engineering –high-throughput computing large scale simulation & parameter studies –Remote software access / Renting Software –Data-intensive computing –On-demand computing

27 27 Conceptual view of the Grid

28 28 How can the Grid help me? Provide access to a global distributed computing environment –via authentication, authorisation, negotiation, security Identify and allocate appropriate resources –interrogate information services -> resource discovery –enquire current status/loading via monitoring tools –decide strategy - eg move data or move application –(co-)allocate resources -> process flow

29 29 How can the Grid help me? (2) Schedule tasks and analyse results –ensure required application code is available on remote machine –transfer or replicate data and update catalogues –monitor execution and resolve problems as they occur –retrieve and analyse results - eg using local visualization

30 30 To make this happen you need … agreed protocols (Grid protocols) defined application programming interfaces (APIs) distributed data management availability of current status of resources monitoring tools accepted authentication procedures and policies network traffic management

31 Grid Components Grid Fabric Networked Resources across Organisations Computers Clusters Data Sources Scientific Instruments Storage Systems Local Resource Managers Operating Systems Queuing Systems TCP/IP & UDP … Libraries & App Kernels … Distributed Resources Coupling Services Comm. Sign on & SecurityInformation … QoS Process Data Access Development Environments and Tools Languages Libraries Debuggers … Web tools Resource BrokersMonitoring Applications and Portals Prob. Solving Env. Scientific … Collaboration Engineering Web enabled Apps Grid Apps. Grid Middleware Grid Tools

32 32 Before the Grid User Application Site A Site B Network The User is responsible for resolving the complexities of the environment independent sites independent hardware and software independent user ids security policy requiring local connection to the machine.

33 33 First Step to the Grid User Application Site A Site B Network Centralized Scheduler and file staging Metacenter Two or more resources connected in a controlled user environment Constraints common architecture single name space common scheduler A layer of abstraction is added that hides some of the complexities associated with running jobs in a distributed computing environment, however, limitations exist

34 34 Grid Middleware User Application Site A Site B Network Infrastructure Common Middleware -abstracts independent, hardware, software, user ids, into a service layer with defined APIs -comprehensive security, -allows for site autonomy -provides a common infrastructure based on middleware The Grid Today 1 Request info from the grid 1 2 Get response 2 3 Make selection and submit job 3 The underlying infrastructure is abstracted into defined APIs thereby simplifying developer and the user access to resources, however, this layer is not intelligent

35 35 The Near Future Grid Grid Middleware - Infrastructure APIs (service oriented) User Application Intelligent, Customized Middleware Site A Site B Network Infrastructure Customizable Grid Services built on defined Infrastructure APIs automatic selection of resources information products tailored to users accountless processing flexible interface: web based, command line, APIs Resources are accessed via various intelligent services that access infrastructure APIs The result: The Scientist and Application Developer can focus on science and not on systems management

36 36 Tom Hinke How the User Sees a Grid A set of grid functions that are available as –Application programmer interfaces (APIs) –Command-line functions After authentication, functions can be used to –Spawn jobs on different processors with a single command –Access data on remote systems –Move data from one processor to another –Support the communication between programs executing on different processors –Discover the properties of computational resources available on the grid using the grid information service –Use a broker to select the best place for a job to run and then negotiate the reservation and execution (coming soon).

37 37 Many GRID Projects and Initiatives PUBLIC FORUMS –Computing Portals –Grid Forum –European Grid Forum –IEEE TFCC! –GRID’2000 and more. Australia –Nimrod/G –EcoGrid and GRACE –DISCWorld Europe –UNICORE –MOL –METODIS –Globe –Poznan Metacomputing –CERN Data Grid –MetaMPI –DAS –JaWS –and many more... Public Grid Initiatives –Distributed.net –SETI@Home –Compute Power Grid USA –Globus –Legion –JAVELIN –AppLes –NASA IPG –Condor –Harness –NetSolve –NCSA Workbench –WebFlow –EveryWhere –and many more... Japan –Ninf –Bricks –and many more... http://www.gridcomputing.com/

38 38

39 39 Nimrod - A Job Management System http://www.dgs.monash.edu.au/~davida/nimrod.html

40 40 Job processing with Nimrod

41 41 Nimrod/G Architecture Middleware Services Nimrod/G Client Grid Information Services Schedule Advisor Trading Manager Nimrod Engine GUSTO Test Bed Persistent Store Grid Explorer GE GIS TM TS RM & TS Dispatcher RM: Local Resource Manager, TS: Trade Server

42 42 User Application Resource Broker A Resource Domain Grid Explorer Schedule Advisor Trade Manager Job Control Agent Deployment Agent Trade Server Resource Allocation Resource Reservation R1R1 Other services Trading Grid Information Server R2R2 RnRn … Charging Alg. Accounting Compute Power Market

43 43 Globus Toolkit Grid computing middleware –Software between the hardware and high-level services –Basic libraries, services, command-line programs Most common middleware used in grids Integrated with Web Service

44 44 Globus Software Architecture Grid SSH Grid FTP login execute commands copy files get and put files 3rd party copy interactive file management parallel transfers Monitoring and Discovery Service (MDS) information about resources and services LDAP distributed directory service single sign on delegation of credentials authorization Grid Security Infrastructure (GSI) SSL/TLSX.509 Certificates authentication secure communication credentials for users, services, hosts execute remote applications stage executable, stdin, stdout, stderr LSFPBS Globus Resource Allocation Manager (GRAM) fork/exe c job management systems

45 45 Globus server system PBS GRAM Server Grid FTP Server Grid SSH Server LSF GRAM Server Grid FTP Server Grid SSH Server Globus server system Globus Deployment Architecture MDS server system MDS GRIS MDS GIIS MDS GRIS Globus client system Clients are programs and libraries GRAM Client Grid FTP Client MDS Client Grid SSH Client UserUser application/tool Web portal

46 46 For More Information Globus Project™ –www.globus.orgwww.globus.org Grid Forum –www.gridforum.orgwww.gridforum.org Book (Morgan Kaufman) –www.mkp.com/grids


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