README.md

AlgorithmSimulator2

Overview

AlgorithmSimulator2 evaluates the performance of the algorithms on various parameters.

The following algorithms are currently supported.

• HEFT
• QL-HEFT
• Proposed algorithm
  • System Model

Usage

1. Create a directory to store the results.

   • ./result/"evaluation_name"/"algorithm_name"
   • 

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.