The theory of directed graphs has developed enormously over recent decades, yet this book (first published in 2000) remains the only book to cover more than a small fraction of the results. New research in the field has made a second edition a necessity. Substantially revised, reorganised and updated, the book now comprises eighteen chapters, carefully arranged in a straightforward and logical manner, with many new results and open problems. As well as covering the theoretical aspects of the subject, with detailed proofs of many important results, the authors present a number of algorithms, and whole chapters are devoted to topics such as branchings, feedback arc and vertex sets, connectivity augmentations, sparse subdigraphs with prescribed connectivity, and also packing, covering and decompositions of digraphs. Throughout the book, there is a strong focus on applications which include quantum mechanics, bioinformatics, embedded computing, and the travelling salesman problem. Detailed indices and topic-oriented chapters ease navigation, and more than 650 exercises, 170 figures and 150 open problems are included to help immerse the reader in all aspects of the subject. Digraphs is an essential, comprehensive reference for undergraduate and graduate students, and researchers in mathematics, operations research and computer science. It will also prove invaluable to specialists in related areas, such as meteorology, physics and computational biology.

Digraphs Theory Algorithms And Applications

The Grid 2: Blueprint for a New Computing Infrastructure

If you want to get Handbook of Internet Computing pdf eBook copy write by good Handbook of Wireless Networks and Mobile Computing Google Books. Mobile Computing General. Handbook of Algorithms for Wireless Networking and Mobile Computing by Azzedine Boukerche (Editor). Call Number: TK 5103.2. CITS4419 Mobile and Wireless Computing software projects related to wireless networks, (2) write technical reports and documentation for complex computer.

Handbook of wireless networks and mobile computing

Thanks to advances in wide-area network technologies and the low cost of computing resources, Grid computing came into being and is currently an active research area. One motivation of Grid computing is to aggregate the power of widely distributed resources, and provide non-trivial services to users. To achieve this goal, an efficient Grid scheduling system is an essential part of the Grid. Rather than covering the whole Grid scheduling area, this survey provides a review of the subject mainly from the perspective of scheduling algorithms. In this review, the challenges for Grid scheduling are identified. First, the architecture of components involved in scheduling is briefly introduced to provide an intuitive image of the Grid scheduling process. Then various Grid scheduling algorithms are discussed from different points of view, such as static vs. dynamic policies, objective functions, applications models, adaptation, QoS constraints, strategies dealing with dynamic behavior of resources, and so on. Based on a comprehensive understanding of the challenges and the state of the art of current research, some general issues worthy of further exploration are proposed.

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Scheduling Algorithms for Grid Computing: State of the Art and Open Problems

Cloud computing has become a significant technology trend Experts believe cloud computing is currently reshaping information technology and the IT marketplace The advantages of using cloud computing include cost savings, speed to market, access to greater computing resources, high availability, and scalability Handbook of Cloud Computing includes contributions from world experts in the field of cloud computing from academia, research laboratories and private industry This book presents the systems, tools, and services of the leading providers of cloud computing; including Google, Yahoo, Amazon, IBM, and Microsoft The basic concepts of cloud computing and cloud computing applications are also introduced Current and future technologies applied in cloud computing are also discussed Case studies, examples, and exercises are provided throughout Handbook of Cloud Computing is intended for advanced-level students and researchers in computer science and electrical engineering as a reference book This handbook is also beneficial to computer and system infrastructure designers, developers, business managers, entrepreneurs and investors within the cloud computing related industry

Handbook of Cloud Computing

The most common objective function of task scheduling problems is makespan. However, on a computational grid, the 2nd optimal makespan may be much longer than the optimal makespan because the computing power of a grid varies over time. So, if the performance measure is makespan, there is no approximation algorithm in general for scheduling onto a grid. In contrast, recently the authors proposed the computing power consumed by a schedule as a criterion of the schedule and, for the criterion, gave (1+m(log/sub e/(m - 1) + 1)/n)-approximation algorithm RR for scheduling n independent coarse-grained tasks with the same length onto a grid with m processors. RR does not use any prediction information on the underlying resources. RR is the first approximation algorithm for grid scheduling. However, so far any performance comparison among related heuristic algorithms is not given. This paper shows experimental results on the comparison of the consumed computing power of a schedule among RR and five related algorithms. It turns out that RR is next to the best of algorithms that need the prediction information on processor speeds and task lengths though RR does not require such information.

A comparison among grid scheduling algorithms for independent coarse-grained tasks

We present a new parallel computational model, named LogGPS, which captures synchronization.The LogGPS model is an extension of the LogGP model, which abstracts communication on parallel platforms. Although the LogGP model captures long messages with one bandwidth parameter (G), it does not capture synchronization that is needed before sending a long message by high-level communication libraries. Our model has one additional parameter, S, defined as the threshold for message length, above which synchronous messages are sent.We also present some experimental results using both models. The results include (1) a verification of the LogGPS model, (2) an example of synchronization analysis using an MPI program and (3) a comparison of the models. The results indicate that the LogGPS model is more accurate than the LogGP model, and analyzing synchronization costs is important when improving parallel program performance.

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LogGPS: a parallel computational model for synchronization analysis

The most common objective function of task scheduling problems is makespan. However, on a computational grid, the 2nd optimal makespan may be much longer than the optimal makespan because the computing power of a grid varies over time. So, if the performance measure is makespan, there is no approximation algorithm in general for scheduling onto a grid. A novel criterion of a schedule is proposed. The proposed criterion is called total processor cycle consumption, which is the total number of instructions the grid could compute until the completion time of the schedule. Moreover, for the criterion, this gives a (l+ m(loge(m-1)+1)/n)-approximation algorithm for scheduling n independent coarse-grained tasks with the same length onto a grid with m processors. The proposed algorithm does not use any prediction information on the performance of underlying resources. This result implies a nontrivial result that the computing power consumed by a parameter sweep application can be limited in such a case within (1+m(loge(m-1)+1)/n) times that required by an optimal schedule, regardless how the speed of each processor varies over time

Near-optimal dynamic task scheduling of independent coarse-grained tasks onto a computational grid

Image registration is a technique for defining a geometric relationship between each point in images. This paper presents a data distributed parallel algorithm that is capable of aligning large-scale three-dimensional (3-D) images of deformable objects. The novelty of our algorithm is to overcome the limitations on the memory space as well as the execution time. In order to enable this, our algorithm incorporates data distribution, data-parallel processing, and load balancing techniques into Schnabel's registration algorithm that realizes robust and efficient alignment based on information theory and adaptive mesh refinement. We also present some experimental results obtained on a 128-CPU cluster of PCs interconnected by Myrinet and Fast Ethernet switches. The results show that our algorithm requires less amount of memory resources, so that aligns datasets up to 1024x1024x590 voxel images with reducing the execution time from hours to minutes, a clinically compatible time.

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A data distributed parallel algorithm for nonrigid image registration

Compute unified device architecture (CUDA) is a software development platform that allows us to run C-like programs on the nVIDIA graphics processing unit (GPU). This paper presents an acceleration method for cone beam reconstruction using CUDA compatible GPUs. The proposed method accelerates the Feldkamp, Davis, and Kress (FDK) algorithm using three techniques: (1) off-chip memory access reduction for saving the memory bandwidth; (2) loop unrolling for hiding the memory latency; and (3) multithreading for exploiting multiple GPUs. We describe how these techniques can be incorporated into the reconstruction code. We also show an analytical model to understand the reconstruction performance on multi-GPU environments. Experimental results show that the proposed method runs at 83% of the theoretical memory bandwidth, achieving a throughput of 64.3 projections per second (pps) for reconstruction of 512^3-voxel volume from 360 512^2-pixel projections. This performance is 41% higher than the previous CUDA-based method and is 24 times faster than a CPU-based method optimized by vector intrinsics. Some detailed analyses are also presented to understand how effectively the acceleration techniques increase the reconstruction performance of a naive method. We also demonstrate out-of-core reconstruction for large-scale datasets, up to 1024^3-voxel volume.

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Kenichi Hagihara

Papers

A comparison among grid scheduling algorithms for independent coarse-grained tasks

LogGPS: a parallel computational model for synchronization analysis

Near-optimal dynamic task scheduling of independent coarse-grained tasks onto a computational grid

A data distributed parallel algorithm for nonrigid image registration

High-performance cone beam reconstruction using CUDA compatible GPUs