• 中国精品科技期刊
  • CCF推荐A类中文期刊
  • 计算领域高质量科技期刊T1类
Advanced Search
Xu Hongzhi, Li Renfa, Zeng Lining. Parallel Task Scheduling for Resource Consumption Minimization with Reliability Constraint[J]. Journal of Computer Research and Development, 2018, 55(11): 2569-2583. DOI: 10.7544/issn1000-1239.2018.20170893
Citation: Xu Hongzhi, Li Renfa, Zeng Lining. Parallel Task Scheduling for Resource Consumption Minimization with Reliability Constraint[J]. Journal of Computer Research and Development, 2018, 55(11): 2569-2583. DOI: 10.7544/issn1000-1239.2018.20170893

Parallel Task Scheduling for Resource Consumption Minimization with Reliability Constraint

More Information
  • Published Date: October 31, 2018
  • Reliability is an important figure of merit for the system and it must be satisfied in safety-critical applications. The systems’ reliability can be improved by resource redundancy, however, it must consume more system resources. The problem of minimizing resource consumption to satisfy reliability goal for parallel applications on heterogeneous systems is investigated. First, the reliability goal of the system is transformed to that of each single task, in which the average worst-case execution time (WCET) of a task on each processor is used as a reference for calculating the reliability goal. Two methods for calculating the reliability goal of each task are proposed for task replication and non-replication. Then, an algorithm of task non-replication for minimizing resource consumption with reliability goal (MRC) is designed. When the system reliability goal requirement isn’t higher than the reachable maximum reliability, the tasks can always be assigned to the appropriate processor so that the reliability goal of the system can be satisfied. Considering that the high-reliability requirements of the system cannot be satisfied by using MRC. Finally, two algorithms for task replication are designed to satisfy system reliability goal. The proposed algorithms are compared with MaxRe, RR, and MRCRG by using real parallel applications and randomly generated parallel applications. Experimental results demonstrate that the proposed algorithms consume fewer resources while satisfying the system reliability goal.
  • Related Articles

    [1]Sun Qingxiao, Yang Hailong. Generalized Stencil Auto-Tuning Framework on GPU Platform[J]. Journal of Computer Research and Development. DOI: 10.7544/issn1000-1239.202440612
    [2]Li Maowen, Qu Guoyuan, Wei Dazhou, Jia Haipeng. Performance Optimization of Neural Network Convolution Based on GPU Platform[J]. Journal of Computer Research and Development, 2022, 59(6): 1181-1191. DOI: 10.7544/issn1000-1239.20200985
    [3]Zhang Shuai, Li Tao, Jiao Xiaofan, Wang Yifeng, Yang Yulu. Parallel TNN Spectral Clustering Algorithm in CPU-GPU Heterogeneous Computing Environment[J]. Journal of Computer Research and Development, 2015, 52(11): 2555-2567. DOI: 10.7544/issn1000-1239.2015.20148151
    [4]Luo Xinyuan, Chen Gang, Wu Sai. A GPU-Accelerated Highly Compact and Encoding Based Database System[J]. Journal of Computer Research and Development, 2015, 52(2): 362-376. DOI: 10.7544/issn1000-1239.2015.20140254
    [5]Tang Liang, Luo Zuying, Zhao Guoxing, and Yang Xu. SOR-Based P/G Solving Algorithm of Linear Parallelism for GPU Computing[J]. Journal of Computer Research and Development, 2013, 50(7): 1491-1500.
    [6]Cai Yong, Li Guangyao, and Wang Hu. Parallel Computing of Central Difference Explicit Finite Element Based on GPU General Computing Platform[J]. Journal of Computer Research and Development, 2013, 50(2): 412-419.
    [7]Wang Zhuowei, Xu Xianbin, Zhao Wuqing, He Shuibing, Zhang Yuping. Parallel Acceleration and Performance Optimization for GRAPES Model Based on GPU[J]. Journal of Computer Research and Development, 2013, 50(2): 401-411.
    [8]Wu Xiaoxiao, Liang Xiaohui, Xu Qidi, and Zhao Qinping. An Algorithm of Physically-based Scalar-fields Guided Deformation on GPU[J]. Journal of Computer Research and Development, 2010, 47(11): 1857-1864.
    [9]Wang Jing, Wang Lili, and Li Shuai. Pre-Computed Radiance Transport All-Frequency Shadows Algorithm on GPU[J]. Journal of Computer Research and Development, 2006, 43(9): 1505-1510.
    [10]Hu Wei and Qin Kaihuai. A New Rendering Technology of GPU-Accelerated Radiosity[J]. Journal of Computer Research and Development, 2005, 42(6): 945-950.

Catalog

    Article views (1108) PDF downloads (496) Cited by()

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return