Dynamic adaptation of parallel codes Toward self-adaptable components for the Grid Françoise André, Jérémy Buisson & Jean-Louis Pazat

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Dynamic adaptation of parallel codes Toward self-adaptable components for the Grid

  • Françoise André, Jérémy Buisson & Jean-Louis Pazat

  • IRISA / INSA de Rennes / Université de Rennes 1


Our view of the Grid



Our view of the Grid



Our view of the Grid

  • Environment that is:

    • Parallel
    • Dynamic
      • Resource allocation may change dynamically
    • Distributed
      • Resources are distributed over a network
      • Resources are in different administration domains
  • Need for a new programming technique

  • Parallel self-adaptable distributed components



Related works

  • Parallel and distributed components / objects exist

    • Example: GridCCM, PARDIS
  • Self-adaptable components exist

    • Example: ACEEL, DART
  • But no parallel and self-adaptable distributed component



Principles of parallel components

  • Encapsulation of a parallel code

    • Collaboration of several communicating processes
  • Goal: allow to easily couple parallel codes



Principles of dynamic adaptation

  • Modification of the executed code

  • Goal: better fit to allocated resources



Dynamic adaptation

  • Three key questions:

    • When should the component adapt?
    • How should the component be modified?
    • Where can the reaction be executed?


Dynamic adaptation

  • When should the component adapt?

    • Upon reception of an event from a monitor
    • According to the policy


Dynamic adaptation

  • How should the component be modified?

    • Executing special code
    • Following directives of the policy


Dynamic adaptation

  • Where can the reaction be executed?



Dynamic adaptation



Mixing parallelism and adaptation



Mixing parallelism and adaptation

  • Introduction of global adaptation points

    • All the processes at the same state
      • Need to coordinate all the processes
  • Example: SPMD code



Mixing parallelism and adaptation

  • Need for a distributed algorithm for the parallel coordinator

    • Only consider globally reachable points
      • In the future of all the processes
    • Make an agreement of all the processes
      • Choose the same point for all the processes


Mixing parallelism and adaptation

  • Need to control the non-determinism

    • Due to parallelism
    • Due to unpredictable conditional instructions
      • Force the result of the conditions if possible
        • Example: insertion of empty iterations in loops
      • Otherwise postpone the decision-making


Experiment

  • Experiment

    • Iterative SPMD code
      • Adaptation points between each iteration
    • Increase of the number of processors
  • Results

    • Negligible time in adaptation points
    • Gain thanks to the adaptation
    • Expected to scale well


Related domains

  • Computation steering

    • Notions equivalent to global adaptation points
      • Need to execute some “special code” at the next “special point”
    • Particular use of adaptation mechanisms
      • User interface instead of monitors


Related domains

  • Fault tolerance

    • Consider dynamic environment
    • Need for a global “consistent” state
      • In the past for fault tolerance
      • In the future for dynamic adaptation
    • Relation to dynamic adaptation
      • An application?
      • A complementary feature?


Work done

  • Design of the overall architecture

    • Identification of functional “boxes”
  • Distributed algorithm for the coordinator

    • Automated instrumentation by static behavioral reification
    • Simple negotiation protocol
  • Demonstration prototype

    • Ad-hoc mechanisms
    • Proof of concept


Future work

  • Generalizing the approach

    • Generic definition of global adaptation points
    • Expression of the adaptation policy
      • Limits of explicit event-based rules
      • Need for more sophisticated (intelligent?) policies
        • Smoothing measures of resource availability
        • Balancing instabilities


Future work

  • Collaborative adaptation of components

    • Control side-effects
      • Avoid adaptation cycles
    • Common policy at the level of:
    • Consider full Grid applications
      • Not only their components


Dynamic adaptation of parallel codes Toward self-adaptable components for the Grid




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