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Advanced Cluster Computing Consortium (AC3) First Annual Meeting “Roadmaps to the Future of Cluster Computing” Held at Cornell Theory Center 2 nd June 2000 Meeting Review by Kenji Takeda ([email protected]) School of Engineering Sciences

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Advanced Cluster Computing Consortium (AC3) First Annual Meeting

“Roadmaps to the Future of Cluster Computing”

Held at Cornell Theory Center

2nd June 2000

Meeting Review by Kenji Takeda ([email protected])

School of Engineering Sciences

The author thanks Microsoft Research for their support


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Talk Outline Meeting

Talk Outline

  • Industry Standard Cluster Computing: R&D to the Enterprise

  • Future of High Performance Computing: Intel Roadmap

  • Cluster Computing Roadmap: Dell

  • Cluster Benchmarks: Dell and CTC

  • Cluster Computing with Windows 2000: MSR

  • Cluster Computing Made Easy: New Tools for Scalable Servers and Services (CTC)

  • Mining Large Databases: Present and Future (CTC)

  • Performance, Scalability and Future Planes: MSTI

  • Cluster Computing at NCSA

  • Panel Sessions

  • Reflections and Conclusions


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Thomas Coleman, Director, Cornell Theory Center Meeting

AC3 Background

  • Cornell Theory Center has many years of supercomputing experience

  • Needed a new mission once IBM SP2 work ended

  • Support computational science and push boundaries

  • Formed AC3 with major industry partners: Dell, Intel and Microsoft

“Increase the space/domain where large-scale problems of computational science are effectively solved using industry standard cluster computing”


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David Lifka, Associate Director, Cornell Theory Center Meeting

Industry Standard Cluster Computing: R&D to the Enterprise

“Cluster computing is ready for Prime Time.

It doesn’t have to be hard” – David Lifka, CTC

  • Proof by example

    • Installed 256 CPU Dell Velocity Cluster with 64 x quad 550MHz Xeons with Giganet interconnect

    • Site-installation took 10 hours

    • Two weeks from installation to full production service

    • Over 100 Cornell projects now use cluster

  • Over 60 corporate partners involved

    • Want to use Windows and move away from UNIX


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David Lifka, Associate Director, Cornell Theory Center Meeting

Industry Standard Solutions

  • Microsoft Windows NT/2000

    • Market volumes drive market in new directions

    • 80% market is Windows NT/2000

    • Administration skill base widely available

    • Future killer apps

    • New generation brought up on Windows. Expect high level of feature functionality and more than a command-line interface

  • Big Iron Supercomputers

    • 4-5 times more expensive than Windows cluster solution

    • High maintenance costs

    • Performance and reliability gap closed


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David Lifka, Associate Director, Cornell Theory Center Meeting

Windows 2000 Issues

  • Major reliability improvements over NT 4.0

  • Windows preserves all aspects of the server market

  • Deployable across the enterprise

  • Coordinated development

  • Desktop to Teraflops with one OS, leading to lower TCO and consistent user interfaces

  • CTC moving all its services to Windows 2000:

    • Email, print servers, backup, file servers, web servers, etc…


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David Lifka, Associate Director, Cornell Theory Center Meeting

CTC Systems Growth

  • AC3 Velocity cluster has spawned huge interest

  • New clusters coming online:

    • Velocity+: 64 x dual 733MHz PIII system with Giganet

    • National Plant Genomics Cluster. 48 CPUs, Gbit ethernet

    • Social Economics Research Cluster: 32 CPUs.Cheaper than upgrading memory on existing SGI system! Looking to move US National Census data servers to Windows 2000 soon

    • AFS servers for Windows 2000: 7 x dual PIII systems

    • 8 serial nodes, Poweredge 2450 servers with 1 Gbyte/node

  • Testing 16- and 32-way systems (Unisys, Sequent and NEC)

  • Early Testing of Itanium and Windows 2000 64-bit


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Timothy Mattson, Senior Research Scientist, Intel Coroporation

Future of High Performance Computing Roadmap: Intel

  • Intel in supercomputer business for a long time

  • ASCI Red still world’s fastest machine,PIII upgrade

  • Changing definition of the supercomputer

    • 1980s: Vector SMP (all custom components)

    • 1990s: MPP (COTS CPUs, everything else custom)

    • 2000s: Clusters (COTS everything)

  • Why has clustering only now taken off:

    • PCs have closed performance gap

    • COTS networking has hit major performance leagues with Gigabit ethernet, Giganet, Myrinet…


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Timothy Mattson, Senior Research Scientist, Intel Coroporation

Intel Processor Roadmap

Itanium highlights

800MHz and up

20 ops/clock cycle

2 Gflops on LINPACK 1000

2.1 Gbytes/s bus for 4-way SMP

128-bit integer and FP registers

Madison

Deerfield

McKinley

Itanium

Future IA32

Foster

Cascades

Xeon


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Timothy Mattson, Senior Research Scientist, Intel Coroporation

COTS Networking: VIA

  • VIA (Virtual Interface Architecture) spearheaded by Intel, MS and Compaq, and 130 other companies

  • Setup direct data channel that bypasses the kernel

  • VIA is here today – mature and stable

  • VIA has its problems though:

    • PCI bottleneck, although improving with 2nd generation PCI-66 cards

    • Targeted at clusters, not mass-market

  • Infiniband is the future….


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Timothy Mattson, Senior Research Scientist, Intel Coroporation

COTS Networking: Infiniband

  • Scalable, high-performance I/O for mass-market

  • Extend native message passing from CPU  Memory  SAN  and beyond…

  • Done using Host Channel Adapter (HCA) to different I/O devices, including other nodes

  • 1st generation devices due Q3 2001

    • Probably not best for HPC. Optimised for small-medium (e-business) clusters

  • Intel aiming “to be the leader in Infiniband for clustering and e-business solutions”

“Infiniband is a great hardware implementation of VIA”


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Timothy Mattson, Senior Research Scientist, Intel Coroporation

Community Cluster Development Kit

  • Clusters are good for research labs but too fiddly

  • They are too hard to setup and use, there is little support, too many options with no clear winners, and too many learning curves to climb

  • Need fully integrated common cluster computing stacks, therefore Intel is supporting the…

    Community Cluster Computing Development Kit

    A snapshot of best-known methods, but not a new standard

    “It’s the software, stupid!”


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Reza Rooholamini, Cluster Development, Dell Coroporation

Cluster Computing Roadmap: Dell

  • Scalable Enterprise Computing

  • Convergence of High Availability and High Performance Computing

  • HPC is a building block for SEC:

    • Firewalls

    • Application clusters

    • Data mining engines


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Reza Rooholamini, Cluster Development, Dell Coroporation

Dell Cluster Solutions

  • HPC Product Approach:

    • Collaborate with universities and research institutes

    • Partner major component providers

    • Prototyping, benchmarking and sizing

    • Case studies and white papers


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JenWei Hsiehi, Cluster Development, Dell and George Coulouris, CTC

Cluster Benchmarks (Dell)

  • 32-CPU Dell test systems:

    • 8 x Dell 6350 4-way SMPs. Fast ethernet, Gigabit ethernet, Giganet and Myrinet

    • 16 x Dell 2450 2-way SMPs. Fast ethernet, Gigabit ethernet, Giganet and Myrinet

  • NAS Parallel benchmarks:

    • Quad-processor significantly slower (30%) than dual processor.

    • Single processors faster than dual processor systems

    • BUT 4-way has best price/performance

  • Giganet (MPI/Pro) better than Myrinet (MPICH-GM)


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JenWei Hsiehi, Cluster Development, Dell and George Coulouris, CTC

Cluster Benchmarks (CTC)

  • Giganet Bandwidth

    • 113 mbytes/s using raw Giganet cLAN driver

    • 87 mbytes/s using MPI/Pro, up to 103 mbytes/s for very large messages

  • NAS Parallel benchmarks:

    • LU and BT scales linearly with Giganet, up to 16 nodes with fast Ethernet


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JenWei Hsiehi, Cluster Development, Dell and George Coulouris, CTC

Real Application Benchmarks (CTC)

ops

  • Protein folding simulations

    • Windows-based visualisation tools developed, see www.tc.cornell.edu/reports/NIH/ resource/CapBiologyTools

  • FEM code with 1.5 million degrees of freedom

    • Superlinear scaling to 128 CPUs with PIII-733MHz and Giganet

    • Per node CPU utilisation decreases as number of SMP CPUs increases

PIII Cluster

speedup

SP2

processors


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Todd Needham, Manager of Research Programs, Microsoft Coulouris, CTC

Cluster Computing with Windows 2000

  • $3 million+ annual commitment to HPC research

  • Supported projects include:

    • MPICH on Windows 2000. Argonne National Labs

    • NCSA VMI driver for Myrinet and Giganet

    • Maui scheduler (from Utah). www.cs.byu.edu

    • UTK: SInRG Grid Environment

    • Globus. Ported to Windows NT. Working on Windows 2000 support using Active Directory services

    • Condor scheduler

    • Parallel visualisation. Kai Li using OpenGL on Windows 2000

    • NCSA. High Performance DCOM over VIA


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Todd Needham, Manager of Research Programs, Microsoft Coulouris, CTC

Enterprise Windows 2000

  • Union of HPC and e-business technology

  • 100% overlap of tools. eg: cluster management

  • Need to improve out-of-the-box experience.

  • MS built 800 CPU Celeron 400MHz cluster to test EP applications and DCOM scalability

  • MSR Cambridge:

    • Performance prediction tools as runtime component in user application

  • MS Redmond:

    • Winsock Direct, data mining, scalable servers


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Todd Needham, Manager of Research Programs, Microsoft Coulouris, CTC

Future Technologies for Windows HPC

  • Parallel file systems

  • Development tools and debuggers

    • Toolworks and Totalview

  • Parallel and Scalable commercial applications

  • Better desktop  cluster transparency. eg: Jack Dongarra’s Excel interface to NetSolve

  • Visual Studio v7. IDE for 3rd party plug-ins

  • 64-bit Windows 2000


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Ken Birman, Professor, Computer Science, Cornell University Coulouris, CTC

Cluster Computing Made Easy: New Tools for Scalable Servers and Services

  • ISIS, HORUS and ENSEMBLE Virtual Synchrony execution model (1987-98)

    • Groups of processes with multicast comms between them

    • Notification of failures and rejoins

    • State transfer, allow addition of nodes to running job

  • HORUS and ENSEMBLE are modular, with plug & play software components

    • NYSE, Swiss Stock Exchange

    • French Air Traffic Control

    • Next Generation AEGIS System


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Ken Birman, Professor, Computer Science, Cornell University Coulouris, CTC

QUINTET

  • Focus on management

  • e-Business solutions. Huge real clusters managed as single entities, such as Hotmail

  • Exploit high performance networks

  • Scalable cluster management

  • Cluster-aware application development

  • Enterprise clusters come in many flavours

    No single management system is suitable for all needs


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Ken Birman, Professor, Computer Science, Cornell University Coulouris, CTC

5 Lessons Learned for Scalability

  • Turn scale to an advantage

  • Progress under all circumstances

  • Avoid transparency side at the server side (it always hurts, the last 5% is impossible)

  • Do not solve all problems in the communications stack

  • Exploit intelligent, non-portable runtimes


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Ken Birman, Professor, Computer Science, Cornell University Coulouris, CTC

Quintet Design

  • Build a component framework for design and construction of cluster management systems

  • Farm Manager

    • node membership and failure detection

    • reliable comms and lightweight state-sharing

  • Farm Services

  • Cluster Designer

    • Tool to construct islands of specialised clusters with farms

    • Generate cluster profiles

    • Collection of User Interfaces and Visualisation tools


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Ken Birman, Professor, Computer Science, Cornell University Coulouris, CTC

Quintet Configuration

  • Automatic component configuration for core comms

    • Exploit SANs

    • Security/secrecy

    • Failure detection

    • Membership consensus

    • Message ordering

  • Consensus membership (on AC3 Velocity cluster)

    • Changes: clean 200 s, dirty 500-7000 s

    • Component membership changes, 50-70 s

    • Fault tolerant distributed lock manager

      • Lock acquire: 70-100 s

      • Node initialisation:400 s for 40,000 locks


Cluster profiles l.jpg

Ken Birman, Professor, Computer Science, Cornell University Coulouris, CTC

Cluster Profiles

  • Application development cluster

    • Process, job, installation and version control

    • Debug service, distributed logging, MS Visual Studio integration and resource measurement

  • Game server cluster

    • 10,000 user Quake server

    • Client management services, application load request routing, synchronisation, state sharing, shared VM services

  • Wolfpack/MS Cluster Services compatible profile

    Quintet first public release (Alpha) in Q3 2000


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Johannes Gehrke, Assistant Professor, Computer Science, Cornell University

Mining Large Databases: Present and Future

  • Data mining reaching maturity.

  • DBMS technology: High availability, maintainability, seamless integration with business processes

  • Current technology:

    • Scalable data mining algorithms

    • Consolidation in the industry

    • Talks about crossing the chasm


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Johannes Gehrke, Assistant Professor, Computer Science, Cornell University

Data Mining: Future Technology

  • Autopilot, automatic algorithms and parameter selection

  • Privacy, internet may provide first tools for users to control access to data about themselves

  • Scalability. Market basket data and ‘clickstream’ data. eg: Yahoo logs 2-4 Gbytes/hr to data mine

  • Data Stream model.

    • Model maintenance

    • Change detection

    • Trend detection, find sequences in slow moving data


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Rossen Dimitrov, MPI Software Technology Cornell University

Performance, Scalability, Future Plans: MPI Software Technology

  • MSTI’s objectives in software design:

    • Performance

    • Scalability

    • Functionality

    • Ease of Use

    • Reliability

    • Robustness

    • Achieve production quality of support at reasonable price

    • Mitigate risk, control cost of ownership


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Rossen Dimitrov, MPI Software Technology Cornell University

MPI/Pro Features

  • User-level thread safety

  • Asynchronous and synchronous completion notification. User runtime switch (½ RTT quoted)

    • Interrupt driven for lower CPU overhead, higher latency (42 s)

    • Polling, low latency, higher CPU utilisation (19 s)

  • Independent message progress

  • Low CPU overhead, high degree of overlapping

  • Optimied collective communications, derived datatype, persistent mode of communications

  • Increased internal concurrency

  • Multi-driver support: Giganet, SMP and TCP


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Rossen Dimitrov, MPI Software Technology Cornell University

MSTI Future Developments

  • Support Model:

    • Value proposition is quality and support

    • Support only model (free downloads available)

    • Goal is to make cluster computing a business

  • MPI/Pro

    • MPI-2 support (2001)

    • Interconnect configuration tool

  • Cluster CoNTroller

    • Time sharing through Windows sessions

    • Gang scheduling

    • Windows 2000 Directory Services


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Rob Pennington, Technical Program Manager, Cluster Computing, NCSA

Cluster Computing at NCSA

  • NCSA, NSF funded National Center 1986-present

  • Large number of parallel computer systems

    • 7 x SGI Origin 2000 systems = 1536 processors

    • 1 x Exemplar = 64 processors

    • 256 processor NT supercluster

    • 100 Windows NT CPUs in test beds and for serial jobs

    • 100 Tbytes disk store. Generate about 1 Tbyte every 2 weeks

  • Applications move easily to clusters, due to source level portability


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Rob Pennington, Technical Program Manager, Cluster Computing, NCSA

Challenges

  • Technical and application challenges

    • Compilers, performance tools, MPI debugging

    • Storage performance, biggest problem as cluster are unbalanced system architectures

    • Administration tools

    • Heterogeneous systems

    • Integration with the Grid

  • Organisational challenges

    • Integration with existing infrastructure

    • Managing user accounts


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Rob Pennington, Technical Program Manager, Cluster Computing, NCSA

Clusters in the Alliance

  • Three large clusters for members of the Alliance

    • NT Supercluster @ NCSA. 256 CPUs

    • Roadrunner cluster @ University of New Mexico. 512 CPUs

    • Argonne National Lab IBM cluster. 512 CPUs

      “Develop locally, run globally”

  • Local clusters used for development and parameter studies

  • Require compatible environments for development and job scheduling across Windows and UNIX

  • Constantly evaluating technologies – OS, CPUs, interconnect, middleware


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Rob Pennington, Technical Program Manager, Cluster Computing, NCSA

Evolution of Cluster Systems

1600+ cluster CPUs

in 2000

192 cluster CPUs

in 1998

  • Job startup streamlined. From 15 mins (in 1998) for 128 node job to 1 minute now

  • Significant user requirement for serial nodes

  • Reliability issues

    • Windows NT nodes NEVER blue screen

    • One hardware failure per 100 machines per month

    • Peripheral failures only, not motherboards or CPUs

    • Use OpenGL cluster monitor tool to keep track of nodes


Ncsa cluster performance l.jpg

Rob Pennington, Technical Program Manager, Cluster Computing, NCSA

NCSA Cluster Performance

  • Quantum Chromo Dynamics memory-intensive code

    • Memory leaks found in HPVM, now fixed (version 1.9)

    • 5% slower using dual CPUs than single CPUs

    • Not suitable for quad-processor systems at all

  • ARPI3D CFD code

    • Code has inefficient MPI. Recoded to improve performance

    • Compute time works well now, MPI part stays constant

    • I/O is a major bottleneck with this code

    • NT Scales better for I/O than Linux


Clusters futures l.jpg

Rob Pennington, Technical Program Manager, Cluster Computing, NCSA

Clusters Futures

  • 2000: Teraflop clusters possible with 1000 1GHz IA-32 nodes

  • 2001: Teraflop machines with around 350 IA-64 nodes (assuming 3 GFlop CPU performance)

  • Major problem is I/O bottleneck though, and SANs are expensive!

  • Possible to use I/O nodes, with fibre-channel and Myrinet TCP to cross-mount file systems


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High Performance Computing with Clusters: Panel Session I Computing, NCSA

  • For big application codes, use Cygwin tools for building (www.sourceware.cygwin.com)

  • Use scripts to wrap native Windows compilers, make them look like UNIX ones

  • Can be tedious to get around compiler flag and filename conventions

  • Wish list:

    • C++ standard compliance

    • C++ compiler robustness

    • Performance and debugging tools


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High Performance Computing with Clusters: Panel Session II Computing, NCSA

  • Molecular dynamics code users are happy:

    • Velocity (550 MHz Xeons) 2.2 - 2.4 faster than previous SP2

    • Velocity+ (733MHz PIII) 1.3 - 1.4 faster than Velocity cluster

  • Intel C compiler about 30% faster than MS Visual C++ on stochastic processes code (lots of random number generation)

  • Windows 2000 runs faster than Windows NT on real applications


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Future for HPC Software on Windows Platform: Panel Session I Computing, NCSA

  • Open question (from NAG), can Windows provide transparent cluster? Pieces are coming together

  • Software vendors cite supporting different flavours of Linux as a problem

  • Intel maintains that HPC is very important to them

  • Todd Needham of Microsoft speculates:

    “Windows 2000 on Itanium Rocks!”

  • Microsoft sees 100% overlap in OS components for Enterprise Computing and HPC


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Future for HPC Software on Windows Platform: Panel Session II

  • MPI Software Technology Inc see many different types of HPC users

    • Support Windows NT, Windows 2000, and different UNIXes

    • Different problems with different OSs

    • Windows: Pinning time for memory higher than Linux. Better security than Linux. Lack of tools on Windows is crippling

    • Linux: SMP support not great. Many variants a problem

  • Windows cluster out-of-the-box experience not great

  • Not many production settings of Windows clusters, so people are not taking it seriously – yet!

  • Beowulf group has a quasi-community that is strong


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Future for HPC Software on Windows Platform: Panel Session III

Five-year prognosis for Windows Clusters

  • Performance + Security + IT + TCO issues prevail

  • Bright future with a level playing field. Good for competition

  • Academia will be biased towards using Linux

  • Outside Academia will be more Windows 2000 oriented

  • User Beware! Petaflop computing will need a new paradigm though, to supersede MPI


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Reflections and Conclusions III

  • Cornell Theory Centre has demonstrated Industry Standard Windows Clusters by example

  • Performance is as good, or better than Big Iron

  • HPC is becoming mainstream as a business tool

  • Convergence in hardware and software between e-business/Enterprise Computing and HPC

  • Cluster management software is maturing fast

  • Lack of software development tools is a key problem


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More Information… III

For more information about Cornell Theory Centre Advanced Cluster Consortium (AC3) see: http://www.tc.cornell.edu/

For more information about Windows Clusters in general see:

http://www.windowsclusters.org


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