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AlgorithmSimulator2

Overview

AlgorithmSimulator2 evaluates the performance of the algorithms on various parameters.

The following algorithms are currently supported.

Usage

  1. Create a directory to store the results.

    • ./result/"evaluation_name"/"algorithm_name"
    • image
  2. Use the following commands depending on the evaluation you want to get.

    • bash change_CCR.sh
      • Evaluation of varying CCR of the input DAG.
      • CCR varies as [0.25, 0.5, 1.0, 2.0, 4.0].
    • bash change_InoutRatio.sh
      • Evaluation of varying the ratio of communication time outside the CC to communication time inside the CC for processors allocated tasks.
      • The ratio varies as [1.5, 3.0, 6.0, 12.0, 24.0]
    • bash change_NumCore.sh
      • Evaluation of varying the number of cores in a single CC for processors allocated tasks.
      • The number of cores varies as [2, 3, 4, 5]
    • bash change_NumNode.sh
      • Evaluation of varying the number of tasks in the input DAG.
      • The number of tasks varies as [20, 50, 100, 200]
    • bash random.sh & python eva_AcceptanceRatio.py
      • Evaluation of acceptance ratio in 50 random DAGs.

Other Files Description

  • ./DAG/~.tgff - Information about the DAGs.
  • class_ClusteredManyCore.py - Processor to which the task is allocated.
  • class_DAG.py - Input DAG.
  • class_Scheduler.py - Scheduler which allocates input DAGs to the processor.
  • class_Q_learning.py - Use Q-learning to obtain the optimal policy.
  • class_Proposed.py - Proposed algorithm.
  • HEFT.py - HEFT algorithm.
  • QLHEFT.py - QL-HEFT algorithm.
  • evaluation.py - Evaluate according to the inputted parameters.
  • order_name.py - Sort the evaluation results.

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