Task Scheduling For Multiprocessor Systems

This book provides a comprehensive overview of both theoretical and pragmatic aspects of resource-allocation and scheduling in multiprocessor and multicore hard-real-time systems. The authors derive new, abstract models of real-time tasks that capture accurately the salient features of real application systems that are to be implemented on multiprocessor platforms, and identify rules for mapping application systems onto the most appropriate models. New run-time multiprocessor scheduling algorithms are presented, which are demonstrably better than those currently used, both in terms of run-time efficiency and tractability of off-line analysis. Readers will benefit from a new design and analysis framework for multiprocessor real-time systems, which will translate into a significantly enhanced ability to provide formally verified, safety-critical real-time systems at a significantly lower cost.

Parallel processing has seen incredible growth with increasingly complex scientific & engg applications coming to their realm.Task scheduling, a key issue for its success,& design of efficient algorithms play a crucial role in it.Due to NP-completeness of the problem research efforts are mainly focussed at heuristic-based approaches to generate near-optimal schedules within reasonable time & resource constraints.Most of the heuristics, however, ignore practical aspect and/or compromise too much on complexity or performance.This monograph provides an in-depth insight into these issues.An overview of state-of-the-art scheduling, reflecting changing paradigms, is also provided.In addition, for scheduling DAG structured applications,3 efficient algorithms are presented & analyzed for homogeneous, heterogeneous & mixed-parallel computing environments.Selective-duplication heuristic is introduced and its usefulness in dealing with IPC overhead is shown in comparison to list, clustering and duplication-based heuristics.An A-cube performance model is suggested to comprehensively study behavior of algorithm, application & architecture in heterogeneous environment.

Simulation studies are used to reveal interesting trade-offs associated with the scheduling algorithm.

Multiprocessor platforms play important roles in modern computing systems, and appear in various applications, ranging from energy-limited hand-held devices to large data centers. As the performance requirements increase, energy-consumption in these systems also increases significantly. Dynamic Voltage and Frequency Scaling (DVFS), which allows processors to dynamically adjust the supply voltage and the clock frequency to operate on different power/energy levels, is considered an effective way to achieve the goal of energy-saving. This book surveys existing works that have been on energy-aware task scheduling on DVFS multiprocessor platforms. Energy-aware scheduling problems are intrinsically optimization problems, the formulations of which greatly depend on the platform and task models under consideration. Thus, Energy-aware Scheduling on Multiprocessor Platforms covers current research on this topic and classifies existing works according to two key standards, namely, homogeneity/heterogeneity of multiprocessor platforms and the task types considered. Under this classification, other sub-issues are also included, such as, slack reclamation, fixed/dynamic priority scheduling, partition-based/global scheduling, and application-specific power consumption, etc.

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.