Load Balancing in Parallel Computers

1. Front Matter

   Pages i-xv

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2. Introduction

   Pages 1-19

3. A Survey of Nearest-Neighbor Load Balancing Algorithms

   Pages 21-35

4. The GDE Method

   Pages 37-51

5. GDE on Tori and Meshes

   Pages 53-78

6. The Diffusion Method

   Pages 79-94

7. GDE Versus Diffusion

   Pages 95-120

8. Termination Detection of Load Balancing

   Pages 121-135

9. Remapping With the GDE Method

   Pages 137-159

10. Load Distribution in Combinatorial Optimizations

    Pages 161-177

11. Conclusions

    Pages 179-186

12. Back Matter

    Pages 187-210

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Load Balancing in Parallel Computers: Theory and Practice is about the essential software technique of load balancing in distributed memory message-passing parallel computers, also called multicomputers. Each processor has its own address space and has to communicate with other processors by message passing. In general, a direct, point-to-point interconnection network is used for the communications. Many commercial parallel computers are of this class, including the Intel Paragon, the Thinking Machine CM-5, and the IBM SP2.
Load Balancing in Parallel Computers: Theory and Practice presents a comprehensive treatment of the subject using rigorous mathematical analyses and practical implementations. The focus is on nearest-neighbor load balancing methods in which every processor at every step is restricted to balancing its workload with its direct neighbours only. Nearest-neighbor methods are iterative in nature because a global balanced state can be reached through processors' successive local operations. Since nearest-neighbor methods have a relatively relaxed requirement for the spread of local load information across the system, they are flexible in terms of allowing one to control the balancing quality, effective for preserving communication locality, and can be easily scaled in parallel computers with a direct communication network.
Load Balancing in Parallel Computers: Theory and Practice serves as an excellent reference source and may be used as a text for advanced courses on the subject.

• algorithms
• computer
• control
• distributed memory
• load balancing
• optimization
• processor

• Wayne State University, USA

  Xu Chengzhong

• The University of Hong Kong, China

  Francis C. M. Lau

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