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Author: Manuel E. Hidalgo Murillo Publisher: ISBN: Category : Multiprocessors Languages : en Pages : 138
Book Description
"In multiprocessor systems, data parallelism is the execution of the same task on data distributed across multiple processors. It involves splitting the data set into smaller data partitions or batches. The process to split the data among the different processors is call “Data Partitioning” and it is an important factor of efficiency for data parallel processing implementation. Data partitioning influences the workload in each processing unit and the network traffic between processes. A poor partition quality can lead to serious performance problems. This research presents a data partitioning method that can be used to improve the performance of data parallel implementations. The proposed method relies on using an initial screening experiment to run a portion of data units. Regression is then used to create a prediction model of the processing times for each data unit. Using the estimated processing time, load balancing is achieved by implementing a greedy algorithm to distribute the units in a parallel environment. Discrete event simulation is used as the application of this research. Comparisons between equal data partitioning and the methodology proposed in this research indicate that time savings and equal load balancing can be achieved."--Abstract.
Author: Manuel E. Hidalgo Murillo Publisher: ISBN: Category : Multiprocessors Languages : en Pages : 138
Book Description
"In multiprocessor systems, data parallelism is the execution of the same task on data distributed across multiple processors. It involves splitting the data set into smaller data partitions or batches. The process to split the data among the different processors is call “Data Partitioning” and it is an important factor of efficiency for data parallel processing implementation. Data partitioning influences the workload in each processing unit and the network traffic between processes. A poor partition quality can lead to serious performance problems. This research presents a data partitioning method that can be used to improve the performance of data parallel implementations. The proposed method relies on using an initial screening experiment to run a portion of data units. Regression is then used to create a prediction model of the processing times for each data unit. Using the estimated processing time, load balancing is achieved by implementing a greedy algorithm to distribute the units in a parallel environment. Discrete event simulation is used as the application of this research. Comparisons between equal data partitioning and the methodology proposed in this research indicate that time savings and equal load balancing can be achieved."--Abstract.
Author: Vishesh Dhingra Publisher: Orange Education Pvt Ltd ISBN: 8197396647 Category : Computers Languages : en Pages : 282
Book Description
TAGLINE Elevate Your Data Analytics Skills, Optimize Workflows, and Drive Informed Decision-Making Across the Spectrum of Data Professions! KEY FEATURES ● Solve practical problems using SAS with real-world case studies that provide hands-on experience. ● Clear, step-by-step tutorials that guide you through various SAS procedures, ensuring easy understanding and application. ● Explore an extensive range of SAS capabilities, from basic data management to advanced analytics and reporting techniques. DESCRIPTION The "Ultimate Statistical Analysis System (SAS) for Data Analytics" is your go-to resource for mastering SAS, a powerful software suite for statistical analysis. This comprehensive book covers everything from the basics of SAS for data professionals to advanced topics like clustering analysis and association rules. With practical examples and clear explanations, this book equips readers with the knowledge and skills needed to excel in their roles as data scientists, analysts, researchers, and more. Whether you're a beginner looking to build a solid foundation in SAS or an experienced user seeking to expand your proficiency, this handbook has something for everyone. You'll learn essential techniques for importing, cleaning, and visualizing data, as well as conducting hypothesis testing, regression analysis, and inferential statistics. Advanced topics like SAS programming concepts and generating reports are also covered in detail, providing readers with the tools to tackle complex data challenges with confidence. With its accessible writing style and emphasis on real-world applications, this book is a practical guide that empowers readers to unlock the full potential of their data. Whether you're analyzing customer behavior, optimizing business processes, or conducting academic research, this handbook will be your trusted companion on the journey to mastering SAS and making informed decisions based on data-driven insights. WHAT WILL YOU LEARN ● Master the skills to import, clean, and transform data using SAS's powerful data manipulation tools. ● Gain the ability to conduct hypothesis testing to build regression models to analyze data relationships. ● Learn to design and produce compelling data visualizations that effectively communicate your data findings. ● Develop proficiency in advanced SAS programming techniques to tackle intricate analytical tasks. ● Discover the use of clustering analysis and association rules to identify meaningful patterns and relationships in your data. ● Generate professional reports to clearly present your analytical results. WHO IS THIS BOOK FOR? This book is ideal for data professionals, analysts, researchers, and anyone seeking to enhance their statistical analysis skills with SAS. Prior familiarity with basic statistical concepts and some experience with data analysis tools would be beneficial for readers to fully leverage the content of this handbook. TABLE OF CONTENTS 1. Introduction to SAS for Data Professionals 2. Data Import and Export in SAS 3. Data Cleaning and Transformation 4. Data Visualizations with SAS 5. Hypothesis Testing and Regression Analysis 6. Descriptive and Inferential Statistics 7. Advanced SAS Programming Concepts 8. Clustering Analysis with PROC CLUSTER 9. Association Rules in SAS 10. Generating Reports in SAS Index
Author: David M. Nicol Publisher: ISBN: Category : Parallel computers Languages : en Pages : 36
Book Description
Abstract: "This paper describes new mapping algorithms for domain-oriented data-parallel computations, where the workload is distributed irregularly throughout the domain, but exhibits localized communication patterns. We consider the problem of partitioning the domain for parallel processing in such a way that the workload on the most heavily loaded processor is minimized, subject to the constraint that the partition be perfectly rectilinear. Rectilinear partitions are useful on architectures that have a fast local mesh network and a relatively slower global network; these partitions heuristically attempt to maximize the fraction of communication carried by the local network. This paper provides an improved algorithm for finding the optimal partition in one dimension, new algorithms for partitioning in two dimensions, and shows that optimal partitioning in three dimensions is NP-complete. We discuss our application of these algorithms to real problems."
Author: Michael Gertz Publisher: Springer Science & Business Media ISBN: 3642138179 Category : Computers Languages : en Pages : 673
Book Description
This book constitutes the proceedings of the 22nd International Conference on Scientific and Statistical Database Management, SSDBM 2010, held in Heidelberg, Germany in June/July 2010. The 30 long and 11 short papers presented were carefully reviewed and selected from 94 submissions. The topics covered are query processing; scientific data management and analysis; data mining; indexes and data representation; scientific workflow and provenance; and data stream processing.
Author: Meikang Qiu Publisher: Springer Nature ISBN: 3030602451 Category : Mathematics Languages : en Pages : 734
Book Description
This three-volume set LNCS 12452, 12453, and 12454 constitutes the proceedings of the 20th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2020, in New York City, NY, USA, in October 2020. The total of 142 full papers and 5 short papers included in this proceedings volumes was carefully reviewed and selected from 495 submissions. ICA3PP is covering the many dimensions of parallel algorithms and architectures, encompassing fundamental theoretical approaches, practical experimental projects, and commercial components and systems. As applications of computing systems have permeated in every aspects of daily life, the power of computing system has become increasingly critical. This conference provides a forum for academics and practitioners from countries around the world to exchange ideas for improving the efficiency, performance, reliability, security and interoperability of computing systems and applications. ICA3PP 2020 focus on two broad areas of parallel and distributed computing, i.e. architectures, algorithms and networks, and systems and applications.
Author: D.J. Hemanth Publisher: IOS Press ISBN: 1643683152 Category : Computers Languages : en Pages : 670
Book Description
Recent developments in parallel computing for various fields of application are providing improved solutions for handling data. These newer, innovative ideas offer the technical support necessary to enhance intellectual decisions, while also dealing more efficiently with the huge volumes of data currently involved. This book presents the proceedings of ICAPTA 2022, the International Conference on Advances in Parallel Computing Technologies and Applications, hosted as a virtual conference from Bangalore, India, on 27 and 28 January 2022. The aim of the conference was to provide a forum for the sharing of knowledge about various aspects of parallel computing in communications systems and networking, including cloud and virtualization solutions, management technologies and vertical application areas. The conference also provided a premier platform for scientists, researchers, practitioners and academicians to present and discuss their most recent innovations, trends and concerns, as well as the practical challenges encountered in this field. More than 300 submissions were received for the conference, from which the 91 full-length papers presented here were accepted after review by a panel of subject experts. Topics covered include parallel computing in communication, machine learning intelligence for parallel computing and parallel computing for software services in theoretical and practical aspects. Providing an overview of recent developments in the field, the book will be of interest to all those whose work involves the use of parallel computing technologies.
Author: Publisher: ISBN: Category : Aeronautics Languages : en Pages : 652
Book Description
Lists citations with abstracts for aerospace related reports obtained from world wide sources and announces documents that have recently been entered into the NASA Scientific and Technical Information Database.
Author: Manuel E. Hidalgo Murillo
Author: Manuel E. Hidalgo Murillo
Author: Vishesh Dhingra
Author: David M. Nicol
Author: Michael Gertz
Author: Meikang Qiu
Author: Foster
Author: Yan Pei
Author: Michael Thuné
Author: D.J. Hemanth
Author: