Название: Task Scheduling for Multi-core and Parallel Architectures: Challenges, Solutions and Perspectives Автор: Quan Chen, Minyi Guo
Издательство: Springer
ISBN: 9811062374
Год: 2017
Страниц: 251
Язык: английский
Формат: pdf, epub
Размер: 10.07 MB
Computers play an indispensable role in almost all scientific fields and disciplines such as biomedicine, physical simulations, computational chemistry, and astronautics. In order to fulfill the urgent requirement for high computational capacity (for example, huge amount of computational capacity is required in big data analysis), technologies of parallel computing and resource management increasingly grow. Nowadays, multi-core processors have become mainstream in both research and real-world settings, from warehouse-scale datacenter, personal desktops, laptops, to smartphones, since they demonstrate the superior performance per watt and the larger computational capacity compared to the traditional single-core processors. For these widely used parallel systems, a key problem is how to schedule the tasks to efficiently utilize the hardware, improve the performance, and guarantee the Quality-of-Service. Because different types of architectures have totally different features, there is not universal scheduling technique that can work the best across all these architectures and different applications. Scheduling techniques often need to be altered to match the various architectures (e.g., multi-core, datacenter, and distributed system) accordingly.
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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