Task Scheduling for Multi-core and Parallel Architectures : Challenges, Solutions and Perspectives /
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 multic...
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| Main Authors: | , |
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| Format: | Electronic eBook |
| Language: | English |
| Published: |
Singapore :
Springer Singapore : Imprint: Springer,
2017.
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| Subjects: | |
| Online Access: | Connect to this title online |
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| 245 | 1 | 0 | |a Task Scheduling for Multi-core and Parallel Architectures : |b Challenges, Solutions and Perspectives / |c by Quan Chen, Minyi Guo. |
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| 505 | 0 | |a Chapter 1 Introduction -- Chapter 2 Conventional Task Scheduling - Chapter 3 Task Scheduling for Multi-socket Architecture -- Chapter 4 Task Scheduling for NUMA-enabled Architecture -- Chapter 5 Task Scheduling for Asymmetric Multi-core Architecture -- Chapter 6 Task Scheduling for Heterogeneous Parallel Architecture - Chapter 7 Task Scheduling for Datacenter -- Chapter 8 Task Scheduling for Distributed System -- Chapter 9 Summary and Perspectives. | |
| 520 | |a 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. | ||
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