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High Performance Cluster Computing: Architectures and Systems

Discover the architectures and systems behind high-performance cluster computing. Learn about scalable parallel computer architectures, resource management, programming environments, and cluster applications. Find out how commodity components and optimized algorithms can improve performance.

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High Performance Cluster Computing: Architectures and Systems

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  1. High Performance Cluster Computing:Architectures and Systems Book Editor: Rajkumar Buyya Slides: Hai Jin and Raj Buyya Internet and Cluster Computing Center

  2. http://www.buyya.com/cluster/ Cluster Computing at a GlanceChapter 1: by M. Baker and R. Buyya • Introduction • Scalable Parallel Computer Architecture • Towards Low Cost Parallel Computing • Windows of Opportunity • A Cluster Computer and its Architecture • Clusters Classifications • Commodity Components for Clusters • Network Service/Communications SW • Middleware and Single System Image • Resource Management and Scheduling • Programming Environments and Tools • Cluster Applications • Representative Cluster Systems • Cluster of SMPs (CLUMPS) • Summary and Conclusions

  3. Resource Hungry Applications • Solving grand challenge applications using computer modeling, simulation and analysis Aerospace Internet & Ecommerce Life Sciences Digital Biology CAD/CAM Military Applications Military Applications Military Applications

  4. Application Categories

  5. How to Run Applications Faster ? • There are 3 ways to improve performance: • Work Harder • Work Smarter • Get Help • Computer Analogy • Using faster hardware • Optimized algorithms and techniques used to solve computational tasks • Multiple computers to solve a particular task

  6. Scalable (Parallel) Computer Architectures • Taxonomy • based on how processors, memory & interconnect are laid out, resources are managed • Massively Parallel Processors (MPP) • Symmetric Multiprocessors (SMP) • Cache-Coherent Non-Uniform Memory Access (CC-NUMA) • Clusters • Distributed Systems – Grids/P2P

  7. Scalable Parallel Computer Architectures • MPP • A large parallel processing system with a shared-nothing architecture • Consist of several hundred nodes with a high-speed interconnection network/switch • Each node consists of a main memory & one or more processors • Runs a separate copy of the OS • SMP • 2-64 processors today • Shared-everything architecture • All processors share all the global resources available • Single copy of the OS runs on these systems

  8. Scalable Parallel Computer Architectures • CC-NUMA • a scalable multiprocessor system having a cache-coherent nonuniform memory access architecture • every processor has a global view of all of the memory • Clusters • a collection of workstations / PCs that are interconnected by a high-speed network • work as an integrated collection of resources • have a single system image spanning all its nodes • Distributed systems • considered conventional networks of independent computers • have multiple system images as each node runs its own OS • the individual machines could be combinations of MPPs, SMPs, clusters, & individual computers

  9. Rise and Fall of Computer Architectures • Vector Computers (VC) - proprietary system: • provided the breakthrough needed for the emergence of computational science, buy they were only a partial answer. • Massively Parallel Processors (MPP) -proprietary systems: • high cost and a low performance/price ratio. • Symmetric Multiprocessors (SMP): • suffers from scalability • Distributed Systems: • difficult to use and hard to extract parallel performance. • Clusters - gaining popularity: • High Performance Computing - Commodity Supercomputing • High Availability Computing - Mission Critical Applications

  10. Top500 Computers Architecture(Clusters share is growing)

  11. The Dead Supercomputer Societyhttp://www.paralogos.com/DeadSuper/ • Dana/Ardent/Stellar • Elxsi • ETA Systems • Evans & Sutherland Computer Division • Floating Point Systems • Galaxy YH-1 • Goodyear Aerospace MPP • Gould NPL • Guiltech • Intel Scientific Computers • Intl. Parallel Machines • KSR • MasPar • ACRI • Alliant • American Supercomputer • Ametek • Applied Dynamics • Astronautics • BBN • CDC • Convex • Cray Computer • Cray Research (SGI?Tera) • Culler-Harris • Culler Scientific • Cydrome • Meiko • Myrias • Thinking Machines • Saxpy • Scientific Computer Systems (SCS) • Soviet Supercomputers • Suprenum Convex C4600

  12. Vendors: Specialised ones (e.g., TMC) disappeared, new emerged

  13. Computer Food Chain: Causing the demise of specialized systems • Demise of mainframes, supercomputers, & MPPs

  14. Towards Clusters The promise of supercomputing to the average PC User ?

  15. Technology Trends... • Performance of PC/Workstations components has almost reached performance of those used in supercomputers… • Microprocessors (50% to 100% per year) • Networks (Gigabit SANs) • Operating Systems (Linux,...) • Programming environments (MPI,…) • Applications (.edu, .com, .org, .net, .shop, .bank) • The rate of performance improvements of commodity systems is much rapid compared to specialized systems

  16. Towards Commodity Cluster Computing • Since the early 1990s, there is an increasing trend to move away from expensive and specialized proprietary parallel supercomputers towards clusters of computers (PCs, workstations) • From specialized traditional supercomputing platforms to cheaper, general purpose systems consisting of loosely coupled components built up from single or multiprocessor PCs or workstations • Linking together two or more computers to jointly solve computational problems

  17. History: Clustering of Computers for Collective Computing PDA Clusters 1990 1995+ 2000+ 1980s 1960

  18. What is Cluster ? • A cluster is a type of parallel and distributed processing system, which consists of a collection of interconnected stand-alone computers cooperatively working together as a single, integrated computing resource. • A node • a single or multiprocessor system with memory, I/O facilities, & OS • A cluster: • generally 2 or more computers (nodes) connected together in a single cabinet, or physically separated & connected via a LAN • appears as a single system to users and applications • provides a cost-effective way to gain features and benefits

  19. PC/Workstation PC/Workstation PC/Workstation PC/Workstation Communications Software Communications Software Communications Software Communications Software Network Interface Hardware Network Interface Hardware Network Interface Hardware Network Interface Hardware Cluster Architecture Parallel Applications Parallel Applications Parallel Applications Sequential Applications Sequential Applications Sequential Applications Parallel Programming Environment Cluster Middleware (Single System Image and Availability Infrastructure) Cluster Interconnection Network/Switch

  20. So What’s So Different about Clusters? • Commodity Parts? • Communications Packaging? • Incremental Scalability? • Independent Failure? • Intelligent Network Interfaces? • Complete System on every node • virtual memory • scheduler • files • … • Nodes can be used individually or jointly...

  21. Windows of Opportunities • Parallel Processing • Use multiple processors to build MPP/DSM-like systems for parallel computing • Network RAM • Use memory associated with each workstation as aggregate DRAM cache • Software RAID • Redundant Array of Inexpensive/Independent Disks • Use the arrays of workstation disks to provide cheap, highly available and scalable file storage • Possible to provide parallel I/O support to applications • Multipath Communication • Use multiple networks for parallel data transfer between nodes

  22. Cluster Design Issues • Enhanced Performance (performance @ low cost) • Enhanced Availability (failure management) • Single System Image (look-and-feel of one system) • Size Scalability (physical & application) • Fast Communication (networks & protocols) • Load Balancing (CPU, Net, Memory, Disk) • Security and Encryption (clusters of clusters) • Distributed Environment (Social issues) • Manageability (admin. and control) • Programmability (simple API if required) • Applicability (cluster-aware and non-aware app.)

  23. Scalability Vs. Single System Image UP

  24. Common Cluster Modes • High Performance (dedicated). • High Throughput (idle cycle harvesting). • High Availability (fail-over). • A Unified System – HP and HA within the same cluster

  25. High Performance Cluster (dedicated mode)

  26. Shared Pool ofComputing Resources:Processors, Memory, Disks Interconnect Guarantee at least oneworkstation to many individuals (when active) Deliver large % of collective resources to few individuals at any one time High Throughput Cluster (Idle Resource Harvesting)

  27. High Availability Clusters

  28. HA and HP in the same Cluster • Best of both Worlds: world is heading towards this configuration)

  29. Cluster Components

  30. Prominent Components of Cluster Computers (I) • Multiple High Performance Computers • PCs • Workstations • SMPs (CLUMPS) • Distributed HPC Systems leading to Grid Computing

  31. System CPUs • Processors • Intel x86-class Processors • Pentium Pro and Pentium Xeon • AMD x86, Cyrix x86, etc. • Digital Alpha – phased out when HP acquired it. • Alpha 21364 processor integrates processing, memory controller, network interface into a single chip • IBM PowerPC • Sun SPARC • Scalable Processor Architecture • SGI MIPS • Microprocessor without Interlocked Pipeline Stages

  32. System Disk • Disk and I/O • Overall improvement in disk access time has been less than 10% per year • Amdahl’s law • Speed-up obtained from faster processors is limited by the slowest system component • Parallel I/O • Carry out I/O operations in parallel, supported by parallel file system based on hardware or software RAID

  33. Commodity Components for Clusters (II): Operating Systems • Operating Systems • 2 fundamental services for users • make the computer hardware easier to use • create a virtual machine that differs markedly from the real machine • share hardware resources among users • Processor - multitasking • The new concept in OS services • support multiple threads of control in a process itself • parallelism within a process • multithreading • POSIX thread interface is a standard programming environment • Trend • Modularity – MS Windows, IBM OS/2 • Microkernel – provides only essential OS services • high level abstraction of OS portability

  34. Prominent Components of Cluster Computers • State of the art Operating Systems • Linux (MOSIX, Beowulf, and many more) • Windows HPC (HPC2N – Umea University) • SUN Solaris (Berkeley NOW, C-DAC PARAM) • IBM AIX (IBM SP2) • HP UX (Illinois - PANDA) • Mach (Microkernel based OS) (CMU) • Cluster Operating Systems (Solaris MC, SCO Unixware, MOSIX (academic project) • OS gluing layers (Berkeley Glunix)

  35. Operating Systems used in Top500 Powerful computers AIX

  36. Prominent Components of Cluster Computers (III) • High Performance Networks/Switches • Ethernet (10Mbps), • Fast Ethernet (100Mbps), • Gigabit Ethernet (1Gbps) • SCI (Scalable Coherent Interface- MPI- 12µsec latency) • ATM (Asynchronous Transfer Mode) • Myrinet (1.28Gbps) • QsNet (Quadrics Supercomputing World, 5µsec latency for MPI messages) • Digital Memory Channel • FDDI (fiber distributed data interface) • InfiniBand

  37. Prominent Components of Cluster Computers (IV) • Fast Communication Protocols and Services (User Level Communication): • Active Messages (Berkeley) • Fast Messages (Illinois) • U-net (Cornell) • XTP (Virginia) • Virtual Interface Architecture (VIA)

  38. Prominent Components of Cluster Computers (V) • Cluster Middleware • Single System Image (SSI) • System Availability (SA) Infrastructure • Hardware • DEC Memory Channel, DSM (Alewife, DASH), SMP Techniques • Operating System Kernel/Gluing Layers • Solaris MC, Unixware, GLUnix, MOSIX • Applications and Subsystems • Applications (system management and electronic forms) • Runtime systems (software DSM, PFS etc.) • Resource management and scheduling (RMS) software • Oracle Grid Engine, Platform LSF (Load Sharing Facility), PBS (Portable Batch Scheduler), Microsoft Cluster Compute Server (CCS)

  39. Advanced Network Services/ Communication SW • Communication infrastructure support protocol for • Bulk-data transport • Streaming data • Group communications • Communication service provides cluster with important QoS parameters • Latency • Bandwidth • Reliability • Fault-tolerance • Network services are designed as a hierarchical stack of protocols with relatively low-level communication API, providing means to implement wide range of communication methodologies • RPC • DSM • Stream-based and message passing interface (e.g., MPI, PVM)

  40. Prominent Components of Cluster Computers (VI) • Parallel Programming Environments and Tools • Threads (PCs, SMPs, NOW..) • POSIX Threads • Java Threads • MPI (Message Passing Interface) • Linux, Windows, on many Supercomputers • Parametric Programming • Software DSMs (Shmem) • Compilers • C/C++/Java • Parallel programming with C++ (MIT Press book) • RAD (rapid application development) tools • GUI based tools for PP modeling • Debuggers • Performance Analysis Tools • Visualization Tools

  41. Prominent Components of Cluster Computers (VII) • Applications • Sequential • Parallel / Distributed (Cluster-aware app.) • Grand Challenging applications • Weather Forecasting • Quantum Chemistry • Molecular Biology Modeling • Engineering Analysis (CAD/CAM) • ………………. • PDBs, web servers, data-mining

  42. Key Operational Benefits of Clustering • High Performance • Expandability and Scalability • High Throughput • High Availability

  43. Clusters Classification (I) • Application Target • High Performance (HP) Clusters • Grand Challenging Applications • High Availability (HA) Clusters • Mission Critical applications

  44. Clusters Classification (II) • Node Ownership • Dedicated Clusters • Non-dedicated clusters • Adaptive parallel computing • Communal multiprocessing

  45. Clusters Classification (III) • Node Hardware • Clusters of PCs (CoPs) • Piles of PCs (PoPs) • Clusters of Workstations (COWs) • Clusters of SMPs (CLUMPs)

  46. Clusters Classification (IV) • Node Operating System • Linux Clusters (e.g., Beowulf) • Solaris Clusters (e.g., Berkeley NOW) • AIX Clusters (e.g., IBM SP2) • SCO/Compaq Clusters (Unixware) • Digital VMS Clusters • HP-UX clusters • Windows HPC clusters

  47. Clusters Classification (V) • Node Configuration • Homogeneous Clusters • All nodes will have similar architectures and run the same OSs • Heterogeneous Clusters • Nodes will have different architectures and run different OSs

  48. Clusters Classification (VI) • Levels of Clustering • Group Clusters (#nodes: 2-99) • Nodes are connected by SAN like Myrinet • Departmental Clusters (#nodes: 10s to 100s) • Organizational Clusters (#nodes: many 100s) • National Metacomputers (WAN/Internet-based) • International Metacomputers (Internet-based, #nodes: 1000s to many millions) • Grid Computing • Web-based Computing • Peer-to-Peer Computing

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