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Author: Gangyi Zhu
Publisher:
ISBN:
Category :
Languages : en
Pages : 163
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Book Description
We start from predicting performance of the disk-based and in-situ parallel data analytics implemented in MapReduce-like frameworks. We take two distinct approaches towards performance prediction. We first expand SKOPE (a SKeleton framewOrk for Performance Exploration) with performance models for disk data read, cache performance, and page fault penalty. Second, an analytical performance model is also developed.
Author: Gangyi Zhu
Publisher:
ISBN:
Category :
Languages : en
Pages : 163
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Book Description
We start from predicting performance of the disk-based and in-situ parallel data analytics implemented in MapReduce-like frameworks. We take two distinct approaches towards performance prediction. We first expand SKOPE (a SKeleton framewOrk for Performance Exploration) with performance models for disk data read, cache performance, and page fault penalty. Second, an analytical performance model is also developed.
Author: Athar Bin Tayyab
Publisher:
ISBN:
Category :
Languages : en
Pages : 298
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Book Description
Author: Xingfu Wu
Publisher: Springer Science & Business Media
ISBN: 1461551471
Category : Computers
Languages : en
Pages : 336
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Book Description
Performance Evaluation, Prediction and Visualization in Parallel Systems presents a comprehensive and systematic discussion of theoretics, methods, techniques and tools for performance evaluation, prediction and visualization of parallel systems. Chapter 1 gives a short overview of performance degradation of parallel systems, and presents a general discussion on the importance of performance evaluation, prediction and visualization of parallel systems. Chapter 2 analyzes and defines several kinds of serial and parallel runtime, points out some of the weaknesses of parallel speedup metrics, and discusses how to improve and generalize them. Chapter 3 describes formal definitions of scalability, addresses the basic metrics affecting the scalability of parallel systems, discusses scalability of parallel systems from three aspects: parallel architecture, parallel algorithm and parallel algorithm-architecture combinations, and analyzes the relations of scalability and speedup. Chapter 4 discusses the methodology of performance measurement, describes the benchmark- oriented performance test and analysis and how to measure speedup and scalability in practice. Chapter 5 analyzes the difficulties in performance prediction, discusses application-oriented and architecture-oriented performance prediction and how to predict speedup and scalability in practice. Chapter 6 discusses performance visualization techniques and tools for parallel systems from three stages: performance data collection, performance data filtering and performance data visualization, and classifies the existing performance visualization tools. Chapter 7 describes parallel compiling-based, search-based and knowledge-based performance debugging, which assists programmers to optimize the strategy or algorithm in their parallel programs, and presents visual programming-based performance debugging to help programmers identify the location and cause of the performance problem. It also provides concrete suggestions on how to modify their parallel program to improve the performance. Chapter 8 gives an overview of current interconnection networks for parallel systems, analyzes the scalability of interconnection networks, and discusses how to measure and improve network performances. Performance Evaluation, Prediction and Visualization in Parallel Systems serves as an excellent reference for researchers, and may be used as a text for advanced courses on the topic.
Author: University of Warwick. Dept. of Computer Science
Publisher:
ISBN:
Category : Chemistry
Languages : en
Pages : 21
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Book Description
Abstract: "This paper presents a methodology for performance prediction of parallel algorithms and illustrates its use on a large scale computational chemistry application. The performance prediction uses a component time characterisation technique which splits up the sequential code into computational components and measures the time for each of them. The parallel algorithm is built from these components by adding communication routines. A "Processor Activity Graph" (PAG) providing a graphical representation of the parallel algorithm runtime behaviour is used for predicting the execution time. For a case study a Self Consistent Field (SCF) computation has been selected which forms the basis of many computational chemistry packages [4,5]. The performance model of SCF computation has been built andthe [sic] predictions have been compared with the results of measurements. The measurements have been provided on a mesh connected distributed memory parallel computer (128 T800 Parsytec Supercluster). The prediction error is less than 10%. Performance optimisation of the application has been achieved by reducing the communication overhead and changing the data representation."
Author: Arun Kumar Sangaiah
Publisher: Academic Press
ISBN: 0128172932
Category : Computers
Languages : en
Pages : 280
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Book Description
Deep Learning and Parallel Computing Environment for Bioengineering Systems delivers a significant forum for the technical advancement of deep learning in parallel computing environment across bio-engineering diversified domains and its applications. Pursuing an interdisciplinary approach, it focuses on methods used to identify and acquire valid, potentially useful knowledge sources. Managing the gathered knowledge and applying it to multiple domains including health care, social networks, mining, recommendation systems, image processing, pattern recognition and predictions using deep learning paradigms is the major strength of this book. This book integrates the core ideas of deep learning and its applications in bio engineering application domains, to be accessible to all scholars and academicians. The proposed techniques and concepts in this book can be extended in future to accommodate changing business organizations’ needs as well as practitioners’ innovative ideas. Presents novel, in-depth research contributions from a methodological/application perspective in understanding the fusion of deep machine learning paradigms and their capabilities in solving a diverse range of problems Illustrates the state-of-the-art and recent developments in the new theories and applications of deep learning approaches applied to parallel computing environment in bioengineering systems Provides concepts and technologies that are successfully used in the implementation of today's intelligent data-centric critical systems and multi-media Cloud-Big data
Author: Peter M.A. Sloot
Publisher: Springer
ISBN: 3540460802
Category : Computers
Languages : en
Pages : 1153
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Book Description
Computational Science is the scienti?c discipline that aims at the development and understanding of new computational methods and techniques to model and simulate complex systems. The area of application includes natural systems – such as biology, envir- mental and geo-sciences, physics, and chemistry – and synthetic systems such as electronics and ?nancial and economic systems. The discipline is a bridge b- ween ‘classical’ computer science – logic, complexity, architecture, algorithms – mathematics, and the use of computers in the aforementioned areas. The relevance for society stems from the numerous challenges that exist in the various science and engineering disciplines, which can be tackled by advances made in this ?eld. For instance new models and methods to study environmental issues like the quality of air, water, and soil, and weather and climate predictions through simulations, as well as the simulation-supported development of cars, airplanes, and medical and transport systems etc. Paraphrasing R. Kenway (R.D. Kenway, Contemporary Physics. 1994): ‘There is an important message to scientists, politicians, and industrialists: in the future science, the best industrial design and manufacture, the greatest medical progress, and the most accurate environmental monitoring and forecasting will be done by countries that most rapidly exploit the full potential ofcomputational science’. Nowadays we have access to high-end computer architectures and a large range of computing environments, mainly as a consequence of the enormous s- mulus from the various international programs on advanced computing, e.g.
Author: David M. Nicol
Publisher:
ISBN:
Category : Computer programming
Languages : en
Pages : 20
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Book Description
Scientific codes are usually parallelized by partitioning a grid among processors. To achieve top performance it is necessary to partition the grid so as to balance workload and minimize communication/synchronization costs. This problem is particularly acute when the grid is irregular, changes over the course of the computation, and is not known until load-time. Critical mapping and remapping decisions rest on our ability to accurately predict performance, given a description of a grid and its partition. This paper discusses one approach to this problem, and illustrates its use on a one-dimensional fluids code. The models we construct are shown empirically to be accurate, and are used to find optimal remapping schedules. Keywords: Parallel processing; Dynamic remapping; Analytic modeling.
Author: Afonso Ferreira
Publisher: Springer Science & Business Media
ISBN: 9783540603214
Category : Computers
Languages : en
Pages : 428
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Book Description
Proceedings -- Parallel Computing.
Author: Gianfranco Bilardi
Publisher: Springer Science & Business Media
ISBN: 9783540631385
Category : Computers
Languages : en
Pages : 306
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Book Description
This book constitutes the refereed proceedings of the 4th International Symposium on Solving Irregularly Structured Problems in Parallel, IRREGULAR'97, held in Paderborn, Germany, in June 1997. The 18 revised full papers presented were carefully selected by the program committee for inclusion in the volume; also included are full papers by the five invited speakers. Among the topics covered are discrete algorithms, randomized methods and approximation algorithms, implementations, programming environments, systems and applications, and scheduling and load balancing.
Author: Alok N. Choudhary
Publisher: CRC Press
ISBN: 9780849389856
Category : Computers
Languages : en
Pages : 338
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Book Description
This three-volume work presents a compendium of current and seminal papers on parallel/distributed processing offered at the 22nd International Conference on Parallel Processing, held August 16-20, 1993 in Chicago, Illinois. Topics include processor architectures; mapping algorithms to parallel systems, performance evaluations; fault diagnosis, recovery, and tolerance; cube networks; portable software; synchronization; compilers; hypercube computing; and image processing and graphics. Computer professionals in parallel processing, distributed systems, and software engineering will find this book essential to their complete computer reference library.
