Charlotte: Metacomputing on the Web

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CharlotteMetacomputing on the Web Arash
Baratloo Mehmet KaraulZvi Kedem
Peter WyckoffNew York University

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Roadmap

• Goals
• Virtual machine model
• Code sample
• Execution environment
• Distributed shared memory
• Experiments
• Summary

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Goals

• Programmers goals
• High level language
• Reliable and predictable virtual machine (fault
  tolerance, heterogeneity of machine types and
  speeds, transiently available machines)
• Portability
• Users goals
• Utilize any machine on the Web (no account or
  shared file system)
• Reliable and predictable virtual machine
• Authentication of results
• CPU donators goals
• Protection from malicious code
• Full control of her resources
• No administrative hassles

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Leveraging Java

• Predictable and reliable virtual machine on top
  of the Java virtual machine
• Java-capable browser widely available
• Emerging standard
• Security
• Heterogeneity
• Portability
• Compilers to appear in the near future

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Virtual Machine Model

• Separation of programming and execution
  environment
• Programmer develops applications for a perfect
  virtual machine
• Slow and fast machines are handled transparently
  by the runtime system
• Transiently available machines handled
  transparently by the runtime system
• Fault tolerance handled transparently by the
  runtime system
• High level programming model
• Unbounded number of parallel routines
• Java plus three simple language constructs
• Distributed shared memory
• Simple memory semantics

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Example Matrix Multiplication
Sample Charlotte Program

• public class MatrixMult extends Droutine
• public static int Size 500
• public Dfloat a new DfloatSizeSize
• public Dfloat b new DfloatSizeSize
• public Dfloat c new DfloatSizeSize
• public void drun(int numTasks, int id)
• int sum
• for(int i0 iltSize i)
• sum 0
• for(int j0 jltSize j)
• sum aidj.get() bji.get()
• cidi.set(sum)

• public void run()
• InitMatrix(a)
• InitMatrix(b)
• parBegin()
• addDroutine(this, Size)
• parEnd()
• PrintMatrix(c)

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Execution Environment

• The same Charlotte program runs on
• a single machine
• multiple machines
• (one user machine and a set of
• potential volunteer machines)
• Interaction among machines solely through
  Java-capable browsers

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Eager Scheduling

• Difficulties in a distributed system
• Detection of crashed-failed machines
• Detection of slow machines
• Solution Eager scheduling
• Volunteer machines contact user machine for work
• Routines may be assigned to multiple machines
• Difficulties with eager scheduling
• Inconsistent memory views across routines and
  different executions of the same routine
• Violation of exactly-once semantics
• Solution Two-phase Idempotent Execution
  Strategy (TIES)

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DSM

• Why DSM?
• Easy to use
• Programmer and user transparent
• Design objectives
• Heterogeneity
• Operating system independence
• Compiler independence
• These require an object-based approach for
  implementing DSM

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DSM Implementation

• Realized at the object level
• All objects have a unique identifier
• Identifiers are identically mapped to objects
  across machines
• Data is transferred on demand
• Granularity can be controlled
• False sharing avoided

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Experiments

• 10 Sun SPARC 5 workstation
• 10 MBit/s Ethernet
• Application Ising model
• Measured time is wall-clock time
• Three tests
• Scalability
• Load balancing
• Transiently available machines

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Experiment 1 Scalability
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Experiment 2 Load balancing
Time
Equivalent Machines
Speedup
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Experiment 3Transient Availability

• Five machines used
• After 100 seconds 1 machine crashed and 1 added
• After another 100 seconds 2 machines crashed and
  2 added
• 90.18 efficiency as opposed to 5 reliable
  machines
• 86.25 efficiency as opposed to sequential
  execution (95.64 for 5 reliable machines)

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Summary

• Charlotte targets the Web
• Leverages benefits of Java (security,
  heterogeneity, widely available, ...)
• Seamlessly crosses administration boundaries
• Distribution of program and data
• DSM with no compiler or OS support