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Current and Emerging Trends in Cluster Computing

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Title: Current and Emerging Trends in Cluster Computing


1
Current and Emerging Trends in Cluster Computing
  • Mark Baker

University of Portsmouth, UK NAG Annual
Symposium, Oxford University 22nd September 2000
http//www.dcs.port.ac.uk/mab/Talks/
2
Talk Content
  • Background and Overview
  • Cluster Architectures
  • Cluster Networking
  • SSI
  • Cluster Tools
  • Conclusions

3
Commodity Cluster Systems
  • Bringing high-end computing to broader problem
    domain - new markets
  • Order of magnitude price/performance advantage.
  • Commodity enabled no long development lead
    times.
  • Low vulnerability to vendor-specific decisions
    companies are ephemeral Clusters are forever !!!

4
Commodity Cluster Systems
  • Rapid response to technology tracking.
  • User-driven configuration-potential for
    application specific ones.
  • Industry-wide, non-proprietary software
    environment.

5
Cluster Architecture
6
Beowulf-class Systems
  • Cluster of PCs
  • Intel x86
  • DEC Alpha
  • Mac Power PC.
  • Pure Mass-Market COTS.
  • Unix-like O/S with source
  • Linux, BSD, Solaris.
  • Message passing programming model
  • MPI, PVM, BSP, homebrews
  • Single user environments.
  • Large science and engineering applications.

7
Decline of Heavy Metal
  • No market for high-end computers
  • minimal growth in last five years.
  • Extinction
  • KSR, TMC, Intel, Meiko, Cray!?, Maspar, BBN,
    Convex
  • Must use COTS
  • Fabrication costs skyrocketing
  • Development lead times too short
  • US Federal Agencies Fleeing
  • NSF, DARPA, DOE, NIST
  • Currently no new good IDEAS.

8
Enabling Drivers
  • Drastic reduction in vendor support for HPC.
  • Component technologies for PCs matches that for
    workstations (in terms of capability).
  • PC hosted software environments similar in
    sophistication and robustness to mainframe OS.
  • Low cost network hardware and software enable
    balanced PC clusters.
  • MPPs establish low-level of expectation.
  • Cross-platform parallel programming model
    (MPI/PVM/HPF).

9
HPC Architectures Top 500
10
Taxonomy
Cluster Computing
11
Beowulf Accomplishments
  • Many Beowulf-class systems installed.
  • Experience gained (implementation/apps).
  • Many applications (some large) routinely executed
    on Beowulfs.
  • Basic software fairly sophisticated and robust.
  • Supports dominant programming/execution paradigm.
  • Single most rapidly growing area in HPC.
  • Ever larger systems in development (_at_SNL).
  • Now recognised as mainstream.

12
Overall Hardware Issues
  • All necessary components available in mass market
    (M2COTS).
  • Powerful computational nodes (SMPs).
  • Network bandwidth impacts high volume
    communication-intensive applications.
  • Network latency impacts random access (with short
    messages) applications.
  • Many applications work well with 1Mbps/Mflop.
  • X10 improvements in bandwidth and latency.
  • Price/Perf. advantage of X10 in many cases.

13
Technology Drivers
  • Reduced recurring costs approx 10 of MPPs.
  • Rapid response to technology advances.
  • Just-in-place configuration and reconfigurable.
  • High reliability if system designed properly.
  • Easily maintained through low cost replacement.
  • Consistent portable programming model
  • Unix, C, Fortran, message passing.
  • Applicable to wide range of problems and
    algorithms.

14
Operating Systems
  • Little work on OSs specifically for clusters.
  • Turnkey clusters are provided with versions of a
    companies mainline products.
  • Typically there may be some form of SSI
    integrated into a conventional OS.
  • Two variants encountered for
  • System administration/job-scheduling purposes -
    middleware that enables each node to deliver the
    required services.
  • Kernel-level e.g., transparent remote device
    usage or to use a distributed storage facility
    that is seen by users as a single standard file
    system.

15
Linux
  • Most popular cluster OS for clusters is Linux.
  • It is free
  • It is an open source - anyone is free to
    customize the kernel to suit ones needs
  • It is easy - large user community users and
    developers have created an abundant number of
    tools, web sites, and documentation, so that
    Linux installation and administration is
    straightforward enough for a typical cluster user.

16
Examples Solaris MC
  • A multi-computer version of their Solaris OS
    called Solaris MC.
  • Incorporates some advances made by Sun, including
    an object-oriented methodology and the use of
    CORBA IDL in the kernel.
  • Consists of a small set of kernel extensions and
    a middleware library - provides SSI to the level
    of the device
  • Processes running on one node can access remote
    devices as if they were local also provides a
    global file system and process space.

17
Examples micro-kernels
  • Another approach is a minimalist approach by
    using micro-kernels - Exokernel is such system.
  • With this approach, only the minimal amount of
    system functionality is built into the kernel -
    allowing services that are needed to be loaded.
  • It maximizes the available physical memory by
    removing undesirable functionality
  • The user can alter the characteristics of the
    service, e.g., a scheduler specific to a cluster
    application may be loaded that helps it run more
    efficiently.

18
How Much of the OS is Needed?
  • This brings up the issue of OS configuration - in
    particular why provide a node OS with the ability
    to provide more services to applications than
    they are ever likely to use?
  • e.g. a user may want to alter the personality of
    the local OS, e.g. "strip down" to a minimalist
    kernel to maximise the available physical memory
    and remove undesired functionality.
  • Mechanisms to achieve this range from
  • Use of a new kernel
  • Dynamically linking service modules into the
    kernel.

19
Networking - Introduction
  • One of the key enabling technologies that has
    established clusters as a dominant force has been
    networking technologies.
  • High performance parallel applications need
    low-latency, high-bandwidth and reliable
    interconnects.
  • Existing LAN/WAN technologies/protocols
    (10/100Mbps Ethernet, ATM) are not well suited to
    support Clusters.
  • Hence the birth of SANs.

20
Comparison
 
 
 AA1I put the references with the text that
describes these.
21
Why Buy a SAN
  • Well, it depends on your application
  • For scientific HPC, Myrinet seems to offer a good
    MBytes/, lots of software and proven
    scalability
  • Synfinity with its best-in-class 1.6 GBytes/s
    could be a valuable alternative for
    small/medium-sized clusters, untried at the
    moment.
  • Windows-based users should give Giganet a try
  • QsNet and ServerNet II are likely the most
    expensive solutions, but an Alpha-based cluster
    from Compaq with one of these should be a good
    number cruncher.

22
Emerging Technologies
  • ATOLL
  • VIA
  • Infiniband
  • Active Networks

23
ATOLL, fully integrated Network in a single chip.
  • New 64/32 bit, 66/33Mhz SAN which aims at the
    single chip solution.
  • All existing components to build a large SAN are
    integrated into one single chip.
  • Includes
  • 4 independent host interfaces
  • 4 network interfaces
  • 8x8 crossbar.

24
ATOLL System Configuration
25
Communications Concerns
  • New Physical Networking Technologies are Fast
  • Gigabit Ethernet, ServerNet, Myrinet
  • Legacy Network Protocol Implementations are Slow
  • System Calls
  • Multiple Data Copies.
  • Communications Gap
  • Systems use a fraction of the available
    performance.

26
Communications Solutions
  • User-level (no kernel) networking.
  • Several Existing Efforts
  • Active Messages (UCB)
  • Fast Messages (UIUC)
  • U-Net (Cornell)
  • BIP (Univ. Lyon, France)
  • Standardization VIA
  • Industry Involvement
  • Killer Clusters.

User Process
OS
NIC
27
VIA
  • VIA is a standard that combines many of the best
    features of various academic projects, and will
    strongly influence the evolution of cluster
    computing.
  • Although VIA can be used directly for application
    programming, it is considered by many systems
    designers to be at too low a level for
    application programming.
  • With VIA, the application must be responsible for
    allocating some portion of physical memory and
    using it effectively.

28
VIA
  • It is expected that most OS and middleware
    vendors will provide an interface to VIA that is
    suitable for application programming.
  • Generally, the interface to VIA that is suitable
    for application programming comes in the form of
    a message-passing interface for scientific or
    parallel programming.

29
What is VIA?
  • Use the kernel for set-ppand get It out of the
    way for send/receive!
  • The Virtual Interface (VI)
  • Protected application-application channel
  • Memory directly accessible by user process.
  • Target Environment
  • LANs and SANs at Gigabit speeds
  • No reliability of underlying media assumed
    (unlike MP fabrics)
  • Errors/Drops assumed to be rare generally fatal
    to VI.

30
InfiniBand - Introduction
  • System bus technologies are beginning to reach
    their limits in terms of speed.
  • Common PCI buses can only support up to 133 Mbps
    across all PCI slots, and even with the 64-bit,
    66 MHz buses available in high-end PC servers,
    566 Mbps of shared bandwidth is the most a user
    can hope for.

31
InfiniBand - Introduction
  • To counter this, a new standard based on switched
    serial links to device groups and devices is
    currently in development.
  • Called InfiniBand, the standard is actually a
    merged proposal of two earlier groups Next
    Generation I/O (NGIO) led by Intel, Microsoft,
    and Sun and Future I/O, supported by Compaq,
    IBM, and Hewlett-Packard.

32
Infiniband - Performance
  • A single InfiniBand link operates at 2.5 Gbps,
    point-to-point in a single direction.
  • Bi-directional links offer twice the throughput
    and can be aggregated together into larger pipes
    of 1 GBytes/ (four co-joined links), or 3
    GBytes/s (12 links).
  • Higher aggregations of links will be possible in
    the future.

33
Active Networks
  • Traditionally, the function of a network has been
    to deliver packets from one end-point to another.
  • Processing within the network has been limited
    largely to routing, simple QOS schemes, and
    congestion control.
  • There is considerable interest in pushing other
    kinds of processing into the network.
  • Examples include the transport-level support for
    wireless links of snoop-TCP and the
    application-specific filtering of network
    firewalls

34
Active Networks
  • Active networks take this trend to the extreme.
  • They allow servers and clients to inject
    customised programs into the nodes of the
    network, thus inter-posing application-specified
    computation between communicating end-points.
  • In this manner, the entire network may be treated
    as part of the overall system that can be
    specialised to achieve application efficiency.

35
Recap
  • Whistle stop tour looked at some of the existing
    and merging network technologies that are being
    used with current clusters.
  • Hardware is more advanced than software that
    comes with it.
  • Software is starting to catch up VIA and Active
    networks are providing performance and
    functionality that todays sophisticated
    applications require.

36
Single System Image (SSI)
  • SSI is the illusion, created by software or
    hardware, that presents a collection of computing
    resources as one whole unified resource.
  • SSI makes the cluster appear like a single
    machine to the user, to applications, and to the
    network.

37
Benefits of SSI
  • Use of system resources transparent.
  • Transparent process migration and load balancing
    across nodes.
  • Potentially improved
  • reliability and higher availability, system
    response time and performance.
  • Simplified system management.
  • Reduction in the risk of operator errors.
  • No need to be aware of the underlying system
    architecture to use these machines effectively.

38
Desired SSI Services
  • Single Entry Point
  • telnet cluster.my_institute.edu
  • telnet node1.cluster. institute.edu
  • Single File Hierarchy /Proc, NFS, xFS, AFS, etc.
  • Single Control Point Management GUI
  • Single memory space - Network RAM/DSM
  • Single Job Management Codine LSF
  • Single GUI Like workstation/PC windowing
    environment it may be Web technology

39
Cluster Tools Introduction
  • Essential that there are numerical libraries and
    programming tools available to application
    developers and system maintainers.
  • Clusters present a different software
    environments on which to build libraries and
    applications, and requires a new level of
    flexibility in the algorithms to achieve adequate
    levels of performance.
  • Many advances and developments in the creation of
    parallel code and tools for distributed memory
    and SMP-based machines.

40
Cluster Tools
  • In most cases, MPI-based libraries and tools will
    operate on cluster, but they may not achieve an
    acceptable level of efficiency or effectiveness
    on clusters that comprise SMP nodes.
  • Little software exists that offers the mixed-mode
    parallelism of distributed SMPs.
  • Need to consider how to create more effective
    libraries and tools for the hybrid clusters.

41
Cluster Tools
  • A major recent architectural innovation is
    clusters of shared-memory multi-processors
    referred to as a Constellation - architectures of
    the ASCI machines, and promise to be the fastest
    general-purpose machines available for the next
    few years.
  • It is the depth of the memory hierarchy with its
    different access primitives and costs at each
    level that makes Constellations more challenging
    to design and use effectively than their SMP and
    MPP predecessors.

42
Cluster Tools
  • Users need a uniform programming environment that
    can be used across uni-processors, SMPs, MPPs,
    and Constellations.
  • Currently, each type of machine has a completely
    different programming model
  • SMPs have dynamic thread libraries with
    communication through shared memory
  • MPPs have SPMD parallelism with message passing
    communication (e.g., MPI)
  • Constellations have the union of these two
    models, requiring that the user write two
    different parallel programs for a single
    application.

43
System Tools
  • The lack of good management tools represents a
    hidden operation cost that is often overlooked.
  • There are numerous tools and techniques available
    for the administration of clusters, few of these
    tools ever see the outside of their developers
    cluster basically they are developed for
    specific in-house tasks.
  • This results in a great deal of duplicated effort
    among cluster administrators and software
    developers.

44
System Tools
  • The tools should provide the look and feel of
    commands issued to a single machine.
  • This is accomplished through using lists, or
    configuration files, to represent the group of
    machines on which a command will operate.

45
System Tools Security
  • Security inside a cluster, between cluster nodes,
    is somewhat relaxed for a number of practical
    reasons.
  • Some of these include
  • Improve performance
  • Ease programming
  • All nodes are generally compromised if one
    cluster nodes security is compromised.
  • Thus, security from outside the cluster into the
    cluster is of utmost concern.

46
System Tools Scalability
  • A user may tolerate an inefficient tool that
    takes minutes to perform an operation across a
    cluster of 8 machines as it is faster than
    performing the operation manually 8 times.
  • However, that user will most likely find it
    intolerable to wait over an hour for the same
    operation to take effect across 128 cluster
    nodes.
  • A further complication is federated clusters
    -extending even further to wide area
    administration.

47
System Tools Some Areas
  • Move disk images from image server to clients.
  • Copy/Move/remove client files.
  • Build a bootable diskette to initially boot a new
    cluster node prior to installation.
  • Secure shell ssh.
  • Cluster-wide ps manipulate cluster-wide
    processes.
  • DHCP, used to allocate IP addresses to machines
    on a given network- lease IP to node.
  • Shutdown/reboot individual nodes.

48
Towards the Future
  • 2 Gflop/s peak processors.
  • 1000 per processor (already there!).
  • 1 Gbps at lt 250 per port.
  • new backplane performance Infiniband!
  • Light-weight communications lt10?s latency (VIA).
  • Optimised math libraries.
  • 1 GByte of main memory per node.
  • 24 Gbytes of disk storage per node.
  • De facto standardised middleware.

49
Million Tflops
  • Today, 3M peak Tflops/s.
  • Before year 2002 1M peak Tflops/s.
  • Performance efficiency is serious challenge
  • System integration
  • does vendor support of massive parallelism have
    to mean massive markup.
  • System administration, boring but necessary.
  • Maintenance without vendors how?
  • New kind of vendors for support.
  • Heterogeneity will become major aspect.

50
Summary of Immediate Challenges
  • There are more costs than recurring costs.
  • Higher level of expertise is required in house.
  • Software environments behind vendor offerings.
  • Tightly coupled systems easier to exploit in some
    cases.
  • Linux model of development scares people.
  • Not yet for everyone.
  • PC-clusters have not achieved maturity.

51
ConclusionsFuture Technology Trends
  • Systems On a Chip (SOC) new Transputers!
  • Multi-GHz processors.
  • 64-bit processors applications.
  • Gbit DRAM.
  • micro-disks on a board.
  • Optical fibre and wave-division multiplexing.
  • Very high bandwidth back-planes.
  • Low-latency/high bandwidth COTS switches.
  • SMP on a chip.
  • Processor In Memory (PIM).

52
The Future
  • Common standards and Open Source software.
  • Better
  • Tools, utilities and libraries
  • Design with minimal risk to accepted standards.
  • Higher degree of portability (standards).
  • Wider range and scope of HPC applications.
  • Wider acceptance of HPC technologies and
    techniques in commerce and industry.
  • Emerging GRID-based environments.

53
Ending
  • Like to thank
  • Thomas Sterling for use of some the materials
    used.
  • Recommend you monitor TFCC activities
    http//www.ieeetfcc.org
  • Join TFCCs mailing list.
  • Send me a reference to your projects.
  • Join in TFCCs efforts (sponsorship, organise
    meetings, contribute to publications).
  • White paper constructive comments please

54
IEEE Computer Society
  • Task Force on Cluster Computing
  • (TFCC)
  • http//www.ieeetfcc.org
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