IPPTS: An Efficient Algorithm for Scientific Workflow Scheduling in Heterogeneous Computing Systems

• Published in: IEEE transactions on parallel and distributed systems Vol. 32; no. 5; pp. 1057 - 1071
• Main Authors: Djigal, Hamza, Feng, Jun, Lu, Jiamin, Ge, Jidong
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.05.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Computation; Dynamic scheduling; Graphs; Heterogeneous networks; heterogeneous systems; Heuristic algorithms; list scheduling; Microprocessors; Prediction algorithms; Priority scheduling; Processors; Program processors; random graphs generator; Schedules; Scheduling; Scheduling algorithms; scientific workflows; Task analysis; Task scheduling; Workflow; Workflow scheduling
• ISSN: 1045-9219; 1558-2183
• DOI: 10.1109/TPDS.2020.3041829

Efficient scheduling algorithms are key for attaining high performance in heterogeneous computing systems. In this article, we propose a new list scheduling algorithm for assigning task graphs to fully connected heterogeneous processors with an aim to minimize the scheduling length. The proposed algorithm, called Improved Predict Priority Task Scheduling (IPPTS) algorithm has two phases: task prioritization phase, which gives priority to tasks, and processor selection phase, which selects a processor for a task. The IPPTS algorithm has a quadratic time complexity as the related algorithms for the same goal, that is <inline-formula><tex-math notation="LaTeX">O(t^{2} \times p)</tex-math> <mml:math><mml:mrow><mml:mi>O</mml:mi><mml:mo>(</mml:mo><mml:msup><mml:mi>t</mml:mi><mml:mn>2</mml:mn></mml:msup><mml:mo>×</mml:mo><mml:mi>p</mml:mi><mml:mo>)</mml:mo></mml:mrow></mml:math><inline-graphic xlink:href="djigal-ieq1-3041829.gif"/> </inline-formula>, for <inline-formula><tex-math notation="LaTeX">t</tex-math> <mml:math><mml:mi>t</mml:mi></mml:math><inline-graphic xlink:href="djigal-ieq2-3041829.gif"/> </inline-formula> tasks and <inline-formula><tex-math notation="LaTeX">p</tex-math> <mml:math><mml:mi>p</mml:mi></mml:math><inline-graphic xlink:href="djigal-ieq3-3041829.gif"/> </inline-formula> processors. Our algorithm reduces the scheduling length significantly by looking ahead in both task prioritization phase and processor selection phase. In this way, the algorithm is looking ahead to schedule a task and its heaviest successor task to the optimistic processor, i.e., the processor that minimizes their computation and communication costs. The experiments based on both randomly generated graphs and graphs of real-world applications show that the IPPTS algorithm significantly outperforms previous list scheduling algorithms in terms of makespan, speedup, makespan standard deviation, efficiency, and frequency of best results.