A hybrid list-based task scheduling scheme for heterogeneous computing

Abstract

Efficient task scheduling is required to attain high performance in both homogeneous and heterogeneous computing systems. An application can be considered as a task grid represented using a Directed Acyclic Graph (DAG). Solving such DAG representing a scheduling problem is an NP-complete task. The primary concern in this problem domain is to reduce the schedule length with minimum complexity. This work presents a Hybrid List-based Task Scheduling using Duplication Scheme (HLTSD) algorithm for heterogeneous processors. The proposed HLTSD algorithm has the same time complexity as that of the recent state-of-the-art algorithms. However, it produces a minimum cost schedule in comparison with other related methods. This work also presents a mathematical formulation to find task priorities. The processor selection phase is improved by utilizing the techniques, like entry task duplication, insertion-based policy, duplication of parent task on other levels, and balancing the load on each processor. The current proposal minimizes the overall makespan of execution by reasonable levels. Performance of the proposed algorithm is evaluated using DAGs adopted from various state-of-the-art algorithms, real-world problems, like Gaussian elimination (GE) and fast Fourier transformation (FFT) task graph and randomly generated graphs with diverse characteristics. The proposed scheme is compared with four state-of-the-art list-based scheduling algorithms, namely Heterogeneous Earliest Finish Time (HEFT), Predict Earliest Finish Time (PEFT), Heterogeneous Scheduling with Improved task Priority (HSIP), and Task Scheduling for Heterogeneous Computing Systems (TSHCS). Based on the best quality schedule, the obtained results suggest that HLTSD has better results in 87% cases.