Author: University of Oregon. Department of Computer and Information Science
Publisher:
ISBN:
Category :
Languages : en
Pages : 8

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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: Holger Brunst
Publisher:
ISBN: 9783832269906
Category :
Languages : en
Pages : 146

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Book Description

Author: Abhinav Bhatele
Publisher: Springer
ISBN: 3030178722
Category : Computers
Languages : en
Pages : 285

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Book Description
This book contains the revised selected papers of 4 workshops held in conjunction with the International Conference on High Performance Computing, Networking, Storage and Analysis (SC) in November 2017 in Denver, CO, USA, and in November 2018 in Dallas, TX, USA: the 6th and 7th International Workshop on Extreme-Scale Programming Tools, ESPT 2017 and ESPT 2018, and the 4th and 5th International Workshop on Visual Performance Analysis, VPA 2017 and VPA 2018. The 11 full papers of ESPT 2017 and ESPT 2018 and the 6 full papers of VPA 2017 and VPA 2018 were carefully reviewed and selected for inclusion in this book. The papers discuss the requirements for exascale-enabled tools as well as new approaches of applying visualization and visual analytic techniques to large-scale applications. Topics of interest include: programming tools; methodologies for performance engineering; tool technologies for extreme-scale challenges (e.g., scalability, resilience, power); tool support for accelerated architectures and large-scale multi-cores; tool infrastructures and environments; evolving/future application requirements for programming tools and technologies; application developer experiences with programming and performance tools; scalable displays of performance data; case studies demonstrating the use of performance visualization in practice; data models to enable scalable visualization; graph representation of unstructured performance data; presentation of high-dimensional data; visual correlations between multiple data sources; human-computer interfaces for exploring performance data; and multi-scale representations of performance data for visual exploration.

Author: Hai-Xiang Lin
Publisher: Springer Science & Business Media
ISBN: 3642141218
Category : Computers
Languages : en
Pages : 472

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Book Description
This book constitutes the workshops of the 15th International Conference on Parallel Computing, Euro-Par 2009, held in Delft, The Netherlands, in August 2009. These focus on advanced specialized topics in parallel and distributed computing and reflect new scientific and technological developments.

Author: Jorge García
Publisher:
ISBN:
Category : Computer vision
Languages : en
Pages : 32

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Book Description

Author: Costas Halatsis
Publisher: Springer Science & Business Media
ISBN: 9783540581840
Category : Computers
Languages : en
Pages : 860

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Book Description
This volume presents the proceedings of the 5th International Conference Parallel Architectures and Languages Europe (PARLE '94), held in Athens, Greece in July 1994. PARLE is the main Europe-based event on parallel processing. Parallel processing is now well established within the high-performance computing technology and of stategic importance not only to the computer industry, but also for a wide range of applications affecting the whole economy. The 60 full papers and 24 poster presentations accepted for this proceedings were selected from some 200 submissions by the international program committee; they cover the whole field and give a timely state-of-the-art report on research and advanced applications in parallel computing.

Author: Michael Alexander
Publisher: Springer
ISBN: 3642297404
Category : Computers
Languages : en
Pages : 502

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Book Description
This book constitutes thoroughly refereed post-conference proceedings of the workshops of the 17th International Conference on Parallel Computing, Euro-Par 2011, held in Bordeaux, France, in August 2011. The papers of these 12 workshops CCPI, CGWS, HeteroPar, HiBB, HPCVirt, HPPC, HPSS HPCF, PROPER, CCPI, and VHPC focus on promotion and advancement of all aspects of parallel and distributed computing.

Author: Gu nter Haring
Publisher: North Holland
ISBN:
Category : Computers
Languages : en
Pages : 380

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Book Description
This volume contains 14 papers presented by researchers from Europe and the USA at the Workshop on Performance Measurement and Visualization of Parallel Systems. The papers focus on approaches for monitoring parallel processing systems and new performance visualization techniques.

Author: Jianping (Kelvin) Li
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Book Description
Visualization helps people to understand data and information. Although computers can efficiently process data, human perception is the key to insight and knowledge discoveries. To meet the challenges of increasingly large and complex data, we need methods that effectively integrates high-performance computing techniques and advanced data analytics into interactive visualization systems for allowing comprehension and communication of massive information. This dissertation contributes new methods and frameworks forempowering visualization systems to facilitate interactive and scalable data analysis. PIX is a stack of toolkits based on these methods and frameworks for building high-performance visualization systems. At the foundation is Portable Processing Pipelines (P3), a new declarative visualization language for rapidly specifying data transformations, visual encodings, and interactions to design visualization applications. Picos builds on P3 to provide a concise declarative grammar and a flexible visual interface for designing hierarchical visualizations for exploratory analysis of complex datasets. To provide high performance for interactive visual analysis, PIX exploits multicore CPUs and manycore GPUs to accelerate data processing and visualization rendering. I developed PeerPower, a parallel and distributed computing framework that effectively utilizes multicore CPUs on heterogeneous systems for accelerating data aggregation and visualization. To harness computing power from GPUs for interactive visualizations, I developed P4 by parallelizing P3 via GPU computing for building high-performance visualization systems using declarative grammars. At runtime, P4 automatically creates GPU programs based on declarative specifications to accelerate both data transformations and visualizations. For interactive analysis of large datasets using limited computing resources, a progressive workflow can be used to provide incrementally refining results and allow steering the analysis process by interacting with the intermediate results. By extending P4, I introduced P5 for providing the capability of parallel and progressive visualization. The extended declarative grammars in P5 allow rapid design of scalable systems for progressive and interactive data analysis. In addition to performance and scalability, visualization systems need to incorporate advanced methods for analyzing complex and high-dimensional datasets. To extend PIX with advanced data analytics, I developed P6, a declarative programming toolkit for specifying and integrating machine learning techniques with interactive visualizations. P6 allows interactive systems to richly and effectively combine the capabilities of humans and computers for data analysis and problem-solving. With PIX, different computing technologies, including parallel computing, progressive analytics, and machine learning, can be easily incorporated into interactive visualization systems. By providing toolkits that are both high performance and easy to use, PIX enables more people to build interactive visualization solutions for analyzing big data.