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© 2017

Task Scheduling for Multi-core and Parallel Architectures

Challenges, Solutions and Perspectives

Benefits

  • Introduces readers to the latest advances in task-scheduling approaches for today’s complex architectures

  • Provides practitioners and professionals valuable experiences and insights on concrete applications to parallel systems

  • Includes original ideas and novel task-scheduling algorithms for the new scenarios of multi-core architectures

  • Discusses current and emerging problems in task-scheduling techniques for complex parallel architectures

Book

Table of contents

  1. Front Matter
    Pages i-xviii
  2. Background

    1. Front Matter
      Pages 1-1
    2. Quan Chen, Minyi Guo
      Pages 3-12
    3. Quan Chen, Minyi Guo
      Pages 13-26
  3. Optimized Task Scheduling for Parallel Architectures

    1. Front Matter
      Pages 27-27
    2. Quan Chen, Minyi Guo
      Pages 29-72
    3. Quan Chen, Minyi Guo
      Pages 73-111
    4. Quan Chen, Minyi Guo
      Pages 153-171
    5. Quan Chen, Minyi Guo
      Pages 173-198
    6. Quan Chen, Minyi Guo
      Pages 199-231
  4. Summary and Discussion

    1. Front Matter
      Pages 233-233
    2. Quan Chen, Minyi Guo
      Pages 235-239
  5. Back Matter
    Pages 241-243

About this book

Introduction

This book presents task-scheduling techniques for emerging complex parallel architectures including heterogeneous multi-core architectures, warehouse-scale datacenters, and distributed big data processing systems. The demand for high computational capacity has led to the growing popularity of multicore processors, which have become the mainstream in both the research and real-world settings. Yet to date, there is no book exploring the current task-scheduling techniques for the emerging complex parallel architectures.

Addressing this gap, the book discusses state-of-the-art task-scheduling techniques that are optimized for different architectures, and which can be directly applied in real parallel systems. Further, the book provides an overview of the latest advances in task-scheduling policies in parallel architectures, and will help readers understand and overcome current and emerging issues in this field.

Keywords

Task scheduling Load balancing Big Data Multicore Datacenter Accelerator Quality-of-Service Distributed computing

Authors and affiliations

  1. 1.Shanghai Jiao Tong UniversityShanghaiChina
  2. 2.Shanghai Jiao Tong UniversityShanghaiChina

About the authors

Quan Chen is currently an assistant professor at the Department of Computer Science and Engineering, Shanghai Jiao Tong University (SJTU), Shanghai, China. Before joining the SJTU, he pursued his post-doctoral research at the University of Michigan’s Department of Computer Science, Ann Arbor, USA from 2014 to 2016. He received his MS degree in 2009 and his PhD degree in 2014, both from the SJTU. During his PhD, he was a research associate at the Department of Computer Science of Columbia University, USA from 2013 to 2014. From 2010 to 2011, he was a visiting scholar at the Department of Computer Science, University of Otago, New Zealand. His research interests include high-performance computing, task scheduling for various architectures, and resource management in datacenters, runtime systems and operating systems. His dissertation was honored with the Shanghai Excellent Doctoral Dissertation Award and the China Computer Federation (CCF) Excellent Doctoral Dissertation Award.

Minyi Guo is a Zhiyuan Chair Professor and head of the Department of Computer Science and Engineering at Shanghai Jiao Tong University (SJTU), Shanghai, China. He is also the director of the SJTU’s Embedded and Pervasive Computing Center. He received his BS and ME degrees in Computer Science from Nanjing University, China in 1982 and 1986, respectively. From 1986 to 1994, he served as an assistant professor at the Department of Computer Science, Nanjing University. He received his PhD degree in Information Science from the University of Tsukuba, Japan in 1998. His research interests include parallel and distributed processing, parallelizing compilers, cloud computing, pervasive computing, software engineering, embedded systems, green computing, and wireless sensor networks. He is an associate editor for IEEE Transactions on Parallel and Distributed Systems (TPDS), Journal of Parallel and Distributed Computing (JPDC), and Journal of Computer Science and Technology (JCST).

He has published numerous articles in prominent journals, and has authored books with Springer. Further, he has led many research projects including Natural Science Foundation of China (NSFC) projects, 863 projects and 973 projects.  

Bibliographic information

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