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Published byEunice Mosley Modified over 9 years ago
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1 SIAC 2000 Program
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2 SIAC 2000 at a Glance AMLunchPMDinner SunCondor MonNOWHPCGlobusClusters TuePVMMPIClustersHPVM WedCondorHPVM
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3 SIAC 2000 Materials: Book 1 David Spector, “Building Linux Clusters: Scaling Linux for Scientific and Enterprise Applications,” August 2000 CD-ROM RedHat Linux, PVM, … O'Reilly & Associates, ISBN: 1565926250
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4 SIAC 2000 Materials: Book 2 Rajkumar Buyya (Editor), “High Performance Cluster Computing: Programming and Applications” Volume 2, June 1999 Prentice Hall; ISBN: 0130137855
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5 SIAC 2000 Materials: Book 3 Selection of papers –Linux clusters –Beowulf HOWTO –PVM, MPI FAQs Handouts from speakers
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6 Introduction to Cluster Computing Prabhaker Mateti Wright State University Dayton, Ohio
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7 Overview High performance computing High throughput computing NOW, HPC, and HTC Parallel algorithms Software technologies
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8 “High Performance” Computing CPU clock frequency Parallel computers Alternate technologies –Optical –Bio –Molecular
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9 “Parallel” Computing Traditional supercomputers –SIMD, MIMD, pipelines –Tightly coupled shared memory –Bus level connections –Expensive to buy and to maintain Cooperating networks of computers
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10 “NOW” Computing Workstation Network Operating System Cooperation Distributed (Application) Programs
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11 Traditional Supercomputers Very high starting cost –Expensive hardware –Expensive software High maintenance Expensive to upgrade
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12 Traditional Supercomputers No one is predicting their demise, but …
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13 Computational Grids are the future
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14 Computational Grids “Grids are persistent environments that enable software applications to integrate instruments, displays, computational and information resources that are managed by diverse organizations in widespread locations.”
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15 Computational Grids Individual nodes can be supercomputers, or NOW High availability Accommodate peak usage LAN : Internet :: NOW : Grid
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16 Globus: A Computational Grid Lee Liming, Argonne Monday, Aug 21, 2000, 1:00 – 5:30 PM
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17 “NOW” Computing Workstation Network Operating System Cooperation Distributed+Parallel Programs
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18 Workstation? PC? Mac?
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19 “Workstation Operating System” Authenticated users Protection of resources Multiple processes Preemptive scheduling Virtual Memory Hierarchical file systems Network centric
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20 Network Ethernet –10 Mbps obsolete –100 Mbps common –1000 Mbps desired Protocols –TCP/IP
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21 Cooperation Workstations are “personal” Others use slows you down … Willing to share Willing to trust
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22 Distributed Programs Spatially distributed programs –A part here, a part there, … –Parallel –Synergy Temporally distributed programs –Compute half today, half tomorrow –Combine the results at the end Migratory programs –Have computation, will travel
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23 Technological Bases of Distributed+Parallel Programs Spatially distributed programs –Message passing Temporally distributed programs –Shared memory Migratory programs –Serialization of data and programs
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24 Distributed Shared Memory “Simultaneous” read/write access by spatially distributed processors Abstraction layer of an implementation built from message passing primitives Semantics not so clean
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25 Technological Bases for Migratory programs Same CPU architecture –X86, PowerPC, MIPS, SPARC, …, JVM Same OS + environment Be able to “checkpoint” –suspend, and –then resume computation –without loss of progress
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26 Development of Distributed+Parallel Programs New code + algorithms Old programs rewritten in new languages that have distributed and parallel primitives Parallelize legacy code
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27 New Programming Languages With distributed and parallel primitives Functional languages Logic languages Data flow languages
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28 Parallel Programming Languages based on the shared-memory model based on the distributed-memory model parallel object-oriented languages parallel functional programming languages concurrent logic languages
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29 PVM, and MPI Message passing primitives Can be embedded in many existing programming languages Architecturally portable Open-sourced implementations
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30 PVM, and MPI Prabhaker Mateti, WSU Tuesday Aug 22, 2000 8:30 – 12:00
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31 OpenMP Distributed shared memory API Implementations: Real soon now http://www.openmp.org/
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32 SPMD Single program, multiple data Contrast with SIMD Same program runs on multiple nodes May or may not be lock-step Nodes may be of different speeds Barrier synchronization
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33 Condor Cooperating workstations Migratory programs –Checkpointing –Remote IO Resource matching
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34 Condor Prabhaker Mateti, WSU Wednesday Aug 22, 2000 8:30 – 12:00
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35 Clusters of Workstations Inexpensive alternative to traditional supercomputers High availability –Lower down time –Easier access Development platform with production runs on traditional supercomputers
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36 Linux Clusters Kumaran Kalyanasundaram, SGI Monday Aug 21, 2000 6:30 – 9:00 PM Tuesday Aug 22, 2000 1:00 – 5:30 PM
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37 HPVM Clusters Mario Lauria Wednesday Aug 23, 2000 1:00 – 4:00 PM
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