The Organic Grid : Self Organizing Computation on a Peer to Peer Network Vikram Negi

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Transcript of The Organic Grid : Self Organizing Computation on a Peer to Peer Network Vikram Negi

  • Slide 1
  • The Organic Grid : Self Organizing Computation on a Peer to Peer Network Vikram Negi
  • Slide 2
  • Distributed Computing Internet Computing Desktop Grids : Scalability SETI@HOME, FOLDING@HOMESETI@HOMEFOLDING@HOME Globus
  • Slide 3
  • Comparison
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  • Problem Focus Schedule Independent Identical subtasks of an Independent Task Application with data in one location NCBI nucleotide nucleotide sequence comparison with BLAST tool.
  • Slide 5
  • Approach Tree Based Adaptive approach Machine configuration, connection bandwidths, network topology (absent) Start Friends Lists ( Build overlay on fly) Biology inspired LALI Principle Positive feedback - Activation Negative feedback - Inhibition
  • Slide 6
  • Approach Initially recruit Friends List Encourage close nodes v/s distant nodes Child nodes give passive feedback to measure effective performance. Continuous on fly adaptation
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  • Basic Design Computation Agent Identifies a child machine. Allocate a subtask(computational process) in child machine(availability). Tree structure Node seeks more subtasks from parent if free. Node send results to parents
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  • Design Maintenance of child lists Seek a balanced tree Rank active children on response times.. Maintain a list of potential children Restructuring of the Overlay Network Maintain a tree Highest throughput closest to root. Push low throughput closer to leaves.
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  • Design Size of Result Burst To determine rank Average over a observation Fault tolerance Maintain list of ancestors Maintain list of unfinished tasks Cycles in the Overlay Network Check the list of ancestors.
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  • Design Termination Root informs all actual, potential and former nodes. Self adjustment of task list size High performance machine request more tasks Prefetching Give time and number estimates of future tasks to parents.
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  • Experiment Set up 18 machine NCBI BLAST application Task : Match 256KB(sequence) with 320 Data chunk 512KB size Subtask match each sequence to chunk
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  • Results The time required for code and the first subtask to arrive at different nodes.
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  • Autonomic ?
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  • Child Propagation
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  • Burst Size Higher Burst Size slows experiment
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  • Prefetch Initial Task Size Ramp up: Time req for subtasks to reach every single node Running Time increases for > 1 prefetch tasks
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  • Self Adjustment
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  • Number of Children Good Initial Configurations no affect on running times.
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  • Discussion Autonomic ? Can we learn from Self Organizing : Bird fly, Fishes swim in pattern Biods : simulation