Predicting Parallel Application Performance Via Machine Learning Approaches

Predicting Parallel Application Performance Via Machine Learning Approaches PDF Author: Karan Singh
Publisher:
ISBN:
Category :
Languages : en
Pages : 74

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Book Description
Consistently growing architectural complexity and machine scales make creating accurate performance models for large-scale applications increasingly challenging. Traditional analytic models are difficult and time-consuming to construct, and are often unable to capture full system and application complexity. To address these challenges, we automatically build models based on execution samples. We use multilayer neural networks, since they can represent arbitrary functions and handle noisy inputs robustly. In this thesis, we focus on two well known parallel applications whose variations in execution times are not well understood: SMG2000, a semicoarsening multigrid solver, and HPL, an open source implementation of LINPACK. We sparsely sample performance data on two radically different platforms across large, multi-dimensional parameter spaces and show that our models based on this data can predict performance within 2% to 7% of actual application runtimes. (Abstract).

Proceedings of the First International Conference on Advanced Data and Information Engineering (DaEng-2013)

Proceedings of the First International Conference on Advanced Data and Information Engineering (DaEng-2013) PDF Author: Tutut Herawan
Publisher: Springer Science & Business Media
ISBN: 9814585181
Category : Technology & Engineering
Languages : en
Pages : 728

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Book Description
The proceeding is a collection of research papers presented at the International Conference on Data Engineering 2013 (DaEng-2013), a conference dedicated to address the challenges in the areas of database, information retrieval, data mining and knowledge management, thereby presenting a consolidated view to the interested researchers in the aforesaid fields. The goal of this conference was to bring together researchers and practitioners from academia and industry to focus on advanced on data engineering concepts and establishing new collaborations in these areas. The topics of interest are as follows but are not limited to: • Database theory • Data management • Data mining and warehousing • Data privacy & security • Information retrieval, integration and visualization • Information system • Knowledge discovery in databases • Mobile, grid and cloud computing • Knowledge-based • Knowledge management • Web data, services and intelligence

Scaling Up Machine Learning

Scaling Up Machine Learning PDF Author: Ron Bekkerman
Publisher: Cambridge University Press
ISBN: 0521192242
Category : Computers
Languages : en
Pages : 493

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Book Description
This integrated collection covers a range of parallelization platforms, concurrent programming frameworks and machine learning settings, with case studies.

Parallel Computing Hits the Power Wall

Parallel Computing Hits the Power Wall PDF Author: Arthur Francisco Lorenzon
Publisher: Springer Nature
ISBN: 303028719X
Category : Computers
Languages : en
Pages : 88

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Book Description
This book describes several approaches to adaptability that are applied for the optimization of parallel applications, such as thread-level parallelism exploitation and dynamic voltage and frequency scaling on multicore systems. This book explains how software developers can apply a novel technique to adapt the number of threads at runtime without any modification in the source code nor recompilation. This book is useful for software developers in general since it offers realistic examples throughout to demonstrate various techniques presented.

New Trends in Information and Communications Technology Applications

New Trends in Information and Communications Technology Applications PDF Author: Safaa O. Al-mamory
Publisher: Springer
ISBN: 3030016536
Category : Computers
Languages : en
Pages : 298

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Book Description
This book constitutes the refereed proceedings of the Third International Conference on New Trends in Information and Communications Technology Applications, NTICT 2018, held in Baghdad, Iraq, in October 2018. The 18 papers presented were carefully reviewed and selected from 86 submissions. The papers are organized in topical sections, namely: Computer networks; system and network security; machine learning; intelligent control system; communication applications; computer vision; and e-learning.

Research and Development in Intelligent Systems XXVI

Research and Development in Intelligent Systems XXVI PDF Author: Richard Ellis
Publisher: Springer Science & Business Media
ISBN: 1848829833
Category : Computers
Languages : en
Pages : 504

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Book Description
The most common document formalisation for text classi?cation is the vector space model founded on the bag of words/phrases representation. The main advantage of the vector space model is that it can readily be employed by classi?cation - gorithms. However, the bag of words/phrases representation is suited to capturing only word/phrase frequency; structural and semantic information is ignored. It has been established that structural information plays an important role in classi?cation accuracy [14]. An alternative to the bag of words/phrases representation is a graph based rep- sentation, which intuitively possesses much more expressive power. However, this representation introduces an additional level of complexity in that the calculation of the similarity between two graphs is signi?cantly more computationally expensive than between two vectors (see for example [16]). Some work (see for example [12]) has been done on hybrid representations to capture both structural elements (- ing the graph model) and signi?cant features using the vector model. However the computational resources required to process this hybrid model are still extensive.

Advances in Computers

Advances in Computers PDF Author: Marvin Zelkowitz
Publisher: Academic Press
ISBN: 0080880304
Category : Computers
Languages : en
Pages : 369

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Book Description
This is volume 72 of Advances in Computers, a series that began back in 1960 and is the oldest continuing series chronicling the ever-changing landscape of information technology. Each year three volumes are produced, which present approximately 20 chapters that describe the latest technology in the use of computers today. In this volume 72, we present the current status in the development of a new generation of high-performance computers. The computer today has become ubiquitous with millions of machines being sold (and discarded) annually. Powerful machines are produced for only a few hundred U.S. dollars, and one of the problems faced by vendors of these machines is that, due to the continuing adherence to Moore’s law, where the speed of such machines doubles about every 18 months, we typically have more than enough computer power for our needs for word processing, surfing the web, or playing video games. However, the same cannot be said for applications that require large powerful machines. Applications such as weather and climate prediction, fluid flow for designing new airplanes or automobiles, or nuclear plasma flow require as much computer power as we can provide, and even that is not enough. Today’s machines operate at the teraflop level (trillions of floating point operations per second) and this book describes research into the petaflop region (1,015 FLOPS). The six chapters provide an overview of current activities that will provide for the introduction of these machines in the years 2011 through 2015.

Programming and Performance Visualization Tools

Programming and Performance Visualization Tools PDF 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.

Performance Tuning of Scientific Applications

Performance Tuning of Scientific Applications PDF Author: David H. Bailey
Publisher: CRC Press
ISBN: 1439815704
Category : Computers
Languages : en
Pages : 395

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Book Description
With contributions from some of the most notable experts in the field, Performance Tuning of Scientific Applications presents current research in performance analysis. The book focuses on the following areas.Performance monitoring: Describes the state of the art in hardware and software tools that are commonly used for monitoring and measuring perf

An Approach to Performance Prediction for Parallel Applications

An Approach to Performance Prediction for Parallel Applications PDF Author: S. A. McKee
Publisher:
ISBN:
Category :
Languages : en
Pages : 12

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Book Description
Accurately modeling and predicting performance for large-scale applications becomes increasingly difficult as system complexity scales dramatically. Analytic predictive models are useful, but are difficult to construct, usually limited in scope, and often fail to capture subtle interactions between architecture and software. In contrast, we employ multilayer neural networks trained on input data from executions on the target platform. This approach is useful for predicting many aspects of performance, and it captures full system complexity. Our models are developed automatically from the training input set, avoiding the difficult and potentially error-prone process required to develop analytic models. This study focuses on the high-performance, parallel application SMG2000, a much studied code whose variations in execution times are still not well understood. Our model predicts performance on two large-scale parallel platforms within 5%-7% error across a large, multi-dimensional parameter space.