Bi-Objective Workflow Scheduling on Heterogeneous Computing Systems Using a Memetic Algorithm

Zhang, Yujian; Tong, Fei; Li, Chuanyou; Xu, Yuwei

doi:10.3390/electronics10020209

Cited by 2 publications

(1 citation statement)

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“…Heterogeneous computing systems are highly competitive because they can provide parallel processing and high performance at a low cost [27], which is one of the reasons why they are widely used in scientific and industrial applications. More than half of the world's top ten supercomputing systems use GPU or CPU accelerator heterogeneous architectures, which are designed to maximize performance and efficiency [28,29]. This also shows that heterogeneous computing systems will continue to be widely concerned and applied.…”

Section: Introductionmentioning

confidence: 99%

List Scheduling Algorithm Based on Virtual Scheduling Length Table in Heterogeneous Computing System

Zhou

Liao

et al. 2021

Wireless Communications and Mobile Computing

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Edge computing needs the close cooperation of cloud computing to better meet various needs. Therefore, ensuring the efficient implementation of applications in cloud computing is not only related to the development of cloud computing itself but also affects the promotion of edge computing. However, resource management and task scheduling strategy are important factors affecting the efficient implementation of applications. Therefore, aiming at the task scheduling problem in cloud computing environment, this paper proposes a new list scheduling algorithm, namely, based on a virtual scheduling length (BVSL) table algorithm. The algorithm first constructs the predicted remaining length table based on the prescheduling results, then constructs a virtual scheduling length table based on the predicted remaining length table, the current task execution cost, and the actual start time of the task, and calculates the task priority based on the virtual scheduling length table to make the overall path the longest task is scheduled first, thus effectively shorten the scheduling length. Finally, the processor is selected for the task based on the predicted remaining length table. The selected processor may not be the earliest for the current task, but it can shorten the finish time of the task in the next phase and reduce the scheduling length. To verify the effectiveness of the scheduling method, experiments were carried out from two aspects: randomly generated graphs and real-world application graphs. Experimental results show that the BVSL algorithm outperforms the latest Improved Predict Priority Task Scheduling (IPPTS) and RE-18 scheduling methods in terms of makespan, scheduling length ratio, speedup, and the number of occurrences of better quality of schedules while maintaining the same time complexity.

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Section: Introductionmentioning

confidence: 99%