Task Scheduling For Parallel Systems
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Task Scheduling for Parallel Systems
A new model for task scheduling that dramatically improves the efficiency of parallel systems Task scheduling for parallel systems can become a quagmire of heuristics, models, and methods that have been developed over the past decades. The author of this innovative text cuts through the confusion and complexity by presenting a consistent and comprehensive theoretical framework along with realistic parallel system models. These new models, based on an investigation of the concepts and principles underlying task scheduling, take into account heterogeneity, contention for communication resources, and the involvement of the processor in communications. For readers who may be new to task scheduling, the first chapters are essential. They serve as an excellent introduction to programming parallel systems, and they place task scheduling within the context of the program parallelization process. The author then reviews the basics of graph theory, discussing the major graph models used to represent parallel programs. Next, the author introduces his task scheduling framework. He carefully explains the theoretical background of this framework and provides several examples to enable readers to fully understand how it greatly simplifies and, at the same time, enhances the ability to schedule. The second half of the text examines both basic and advanced scheduling techniques, offering readers a thorough understanding of the principles underlying scheduling algorithms. The final two chapters address communication contention in scheduling and processor involvement in communications. Each chapter features exercises that help readers put their new skills into practice. An extensive bibliography leads to additional information for further research. Finally, the use of figures and examples helps readers better visualize and understand complex concepts and processes. Researchers and students in distributed and parallel computer systems will find that this text dramatically improves their ability to schedule tasks accurately and efficiently.
Optimal Task Scheduling for Parallel Systems Using State-space Search
It is of ever-increasing importance that programs are able to take full advantage of the parallel systems on which they are run. Task scheduling is the problem of producing a schedule for a program, such that the tasks which make up the program are each allocated to a specific processor and in a specific order which minimises the overall run-time. This problem is NP-hard, so that the amount of work required grows exponentially as the number of tasks is increased. Although the NP-hardness of the problem usually discourages optimal solving, an optimal schedule can give a significant advantage in time critical systems or applications where a single schedule is reused many times. Previous research with branch-and-bound for optimal task scheduling has shown promise with small task graphs, being competitive with other methods. The state-space model used in that work has an obvious drawback of allowing many duplicate states to occur in the state-space, which theoretically causes a large amount of additional time and memory to be required. This thesis proposes a new state-space model called Allocation-Ordering (AO), which improves on older models through its carefully designed lack of duplicate states. AO divides the task scheduling problem into two distinct sub-problems (allocation and ordering) which are handled in sequence within the state-space. Experimental evaluation confirms the benefits of the model. The benefits of AO’s lack of duplicate states for other branch and bound algorithms are then explored, specifically variants with interesting properties such as parallelisation and low memory requirements. We then investigate its applicability to more complex task scheduling models: the model is first adapted to allow optimal task scheduling with related heterogeneous processors, and then to allow optimal task scheduling with task duplication. The success of the adaptation of AO shows its flexibility, and suggests it may have wide applicability to variants of the task scheduling problem, and potentially other problems.
Scheduling for Parallel Processing
Author: Maciej Drozdowski
language: en
Publisher: Springer Science & Business Media
Release Date: 2010-03-14
Overview and Goals This book is dedicated to scheduling for parallel processing. Presenting a research ?eld as broad as this one poses considerable dif?culties. Scheduling for parallel computing is an interdisciplinary subject joining many ?elds of science and te- nology. Thus, to understand the scheduling problems and the methods of solving them it is necessary to know the limitations in related areas. Another dif?culty is that the subject of scheduling parallel computations is immense. Even simple search in bibliographical databases reveals thousands of publications on this topic. The - versity in understanding scheduling problems is so great that it seems impossible to juxtapose them in one scheduling taxonomy. Therefore, most of the papers on scheduling for parallel processing refer to one scheduling problem resulting from one way of perceiving the reality. Only a few publications attempt to arrange this ?eld of knowledge systematically. In this book we will follow two guidelines. One guideline is a distinction - tween scheduling models which comprise a set of scheduling problems solved by dedicated algorithms. Thus, the aim of this book is to present scheduling models for parallel processing, problems de?ned on the grounds of certain scheduling models, and algorithms solving the scheduling problems. Most of the scheduling problems are combinatorial in nature. Therefore, the second guideline is the methodology of computational complexity theory. Inthisbookwepresentfourexamplesofschedulingmodels. Wewillgodeepinto the models, problems, and algorithms so that after acquiring some understanding of them we will attempt to draw conclusions on their mutual relationships.