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Tools for High Performance Computing 2009, Matthias S. M?ller; Michael M. Resch; Alexander Sc


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Автор: Matthias S. M?ller; Michael M. Resch; Alexander Sc
Название:  Tools for High Performance Computing 2009
ISBN: 9783642437526
Издательство: Springer
Классификация:



ISBN-10: 3642437524
Обложка/Формат: Paperback
Страницы: 184
Вес: 0.29 кг.
Дата издания: 07.10.2014
Язык: English
Размер: 234 x 156 x 11
Основная тема: Computer Science
Подзаголовок: Proceedings of the 3rd International Workshop on Parallel Tools for High Performance Computing, September 2009, ZIH, Dresden
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: PERISCOPE: An Online-Based Distributed Performance Analysis Tool.- Comprehensive Performance Tracking with Vampir 7.- Performance Analysis and Workload Characterization with IPM.- Recent Developments in the Scalasca Toolset.- MUST: A Scalable Approach to Runtime Error Detection in MPI Programs.- HPC Profiling with the Sun Studio(TM) Performance Tools.- Performance Tuning of x86 OpenMP Codes with MAQAO.- Scalable Parallel Debugging with g-Eclipse.- New Analysis Techniques in the CEPBA-Tools Environment.- The Importance of Run-Time Error Detection.- Collecting Performance Data with PAPI-C.- ISP Tool Update: Scalable MPI Verification.

Tools for High Performance Computing 2011

Автор: Holger Brunst; Matthias S. M?ller; Wolfgang E. Nag
Название: Tools for High Performance Computing 2011
ISBN: 3642439853 ISBN-13(EAN): 9783642439858
Издательство: Springer
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Цена: 130430.00 T
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Описание: The proceedings of the 5th International Workshop on Parallel Tools for High Performance Computing provide an overview on supportive software tools and environments in the fields of System Management, Parallel Debugging and Performance Analysis.

High Performance Computing

Автор: Kunkel
Название: High Performance Computing
ISBN: 3319413201 ISBN-13(EAN): 9783319413204
Издательство: Springer
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Цена: 59630.00 T
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Описание: This book constitutes the refereed proceedings of the 31st International Conference, ISC High Performance 2016 [formerly known as the International Supercomputing Conference] held in Frankfurt, Germany, in June 2016. The 25 revised full papers presented in this book were carefully reviewed and selected from 60 submissions.

High-Performance Scientific Computing

Автор: Edoardo Di Napoli; Marc-Andr? Hermanns; Hristo Ili
Название: High-Performance Scientific Computing
ISBN: 3319538616 ISBN-13(EAN): 9783319538617
Издательство: Springer
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Цена: 51230.00 T
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Описание: This book constitutes the thoroughly refereed post-conference proceedings of the First JARA High-Performance Computing Symposium, JARA-HPC 2016, held in Aachen, Germany, in October 2016. The 21 full papers presented were carefully reviewed and selected from 26 submissions.

High Performance Computing Systems. Performance Modeling, Benchmarking and Simulation

Автор: Stephen A. Jarvis; Steven A. Wright; Simon D. Hamm
Название: High Performance Computing Systems. Performance Modeling, Benchmarking and Simulation
ISBN: 3319102133 ISBN-13(EAN): 9783319102139
Издательство: Springer
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Цена: 52170.00 T
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Описание: The selected articles broadly cover topics on massively parallel and high-performance simulations, modeling and simulation, model development and analysis, performance optimization, power estimation and optimization, high performance computing, reliability, performance analysis, and network simulations.

High Performance Computing

Автор: Julian M. Kunkel; Thomas Ludwig
Название: High Performance Computing
ISBN: 3319201182 ISBN-13(EAN): 9783319201184
Издательство: Springer
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Цена: 67080.00 T
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Описание: Asynchronous Iterative Algorithm for Computing Incomplete Factorizations on GPUs.- Matrix Multiplication on High-Density Multi-GPU Architectures: Theoretical and Experimental Investigations.- A Framework for Batched and GPU-Resident Factorization Algorithms Applied to Block Householder Transformations.- Parallel Efficient Sparse Matrix-Matrix Multiplication on Multicore Platforms.- On the Design, Development, and Analysis of Optimized Matrix-Vector Multiplication Routines for Coprocessors.- Large-Scale Neo-Heterogeneous Programming and Optimization of SNP Detection on Tianhe-2.- ACCOLADES: A Scalable Workflow Framework for Large-Scale Simulation and Analyses of Automotive Engines.- Accelerating LBM and LQCD Application Kernels by In-Memory Processing.- On Quantum Chemistry Code Adaptation for RSC PetaStream Architecture.- Dtree: Dynamic Task Scheduling at Petascale.- Feasibility Study of Porting a Particle Transport Code to FPGA.- A Scalable, Linear-Time Dynamic Cutoff Algorithm for Molecular Dynamics.- BWTCP: A Parallel Method for Constructing BWT in Large Collection of Genomic Reads.- Lattice-CSC: Optimizing and Building an Efficient Supercomputer for Lattice-QCD and to Achieve First Place in Green500.- An Efficient Clique-Based Algorithm of Compute Nodes Allocation for In-memory Checkpoint System.- A Scalable Algorithm for Radiative Heat Transfer Using Reverse Monte Carlo Ray Tracing.- Optimizing Processes Mapping for Tasks with Non-uniform Data Exchange Run on Cluster with Different Interconnects.- Dynamically Adaptable I/O Semantics for High Performance Computing.- Predicting Performance of Non-contiguous I/O with Machine Learning.- A Best Practice Analysis of HDF5 and NetCDF-4 Using Lustre.- Striping Layout Aware Data Aggregation for High Performance I/O on a Lustre File System.- Hop: Elastic Consistency for Exascale Data Stores.- Energy-Efficient Data Processing Through Data Sparsing with Artifacts.- Updating the Energy Model for Future Exascale Systems.- High-Order ADER-DG Minimizes Energy- and Time-to-Solution of SeisSol.- Modeling the Productivity of HPC Systems on a Computing Center Scale.- Taking Advantage of Node Power Variation in Homogenous HPC Systems to Save Energy.- A Run-Time System for Power-Constrained HPC Applications.- A Machine Learning Approach for a Scalable, Energy-Efficient Utility-Based Cache Partitioning.- A Case Study - Cost of Preemption for Urgent Computing on SuperMUC.- Designing Non-blocking Personalized Collectives with Near Perfect Overlap for RDMA-Enabled Clusters.- Design Methodology for Optimizing Optical Interconnection Networks in High Performance Systems.- Quantifying Communication in Graph Analytics.- Formal Metrics for Large-Scale Parallel Performance.- Hunting Down Load Imbalance: A Moving Target.- Orchestrating Docker Containers in the HPC Environment.- Performance and Scaling of WRF on Three Different Parallel Supercomputers.

Tools for High Performance Computing 2016

Автор: Christoph Niethammer; Jos? Gracia; Tobias Hilbrich
Название: Tools for High Performance Computing 2016
ISBN: 3319567012 ISBN-13(EAN): 9783319567013
Издательство: Springer
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Цена: 130430.00 T
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Описание: This book presents the proceedings of the 10th International Parallel Tools Workshop, held October 4-5, 2016 in Stuttgart, Germany - a forum to discuss the latest advances in parallel tools.High-performance computing plays an increasingly important role for numerical simulation and modelling in academic and industrial research.

Introduction to High Performance Computing for Scientists and Engineers

Автор: Hager
Название: Introduction to High Performance Computing for Scientists and Engineers
ISBN: 143981192X ISBN-13(EAN): 9781439811924
Издательство: Taylor&Francis
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Цена: 80630.00 T
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Описание: Written by HPC experts, this book provides a solid introduction to current mainstream computer architecture, dominant parallel programming models, and useful optimization strategies for scientific HPC. It facilitates an intuitive understanding of performance limitations without relying on heavy computer science knowledge.

High Performance Computing Systems and Applications

Автор: Douglas J. K. Mewhort; Natalie M. Cann; Gary W. Sl
Название: High Performance Computing Systems and Applications
ISBN: 3642126588 ISBN-13(EAN): 9783642126581
Издательство: Springer
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Цена: 83850.00 T
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Описание: Constitutes the refereed post-conference proceedings of the 23rd International Symposium on High Performance Computing Systems and Applications, HPCS 2009, held in Kingston, Canada, in June 2009.

High Performance Computing in Science and Engineering

Автор: Kozubek
Название: High Performance Computing in Science and Engineering
ISBN: 3319403605 ISBN-13(EAN): 9783319403601
Издательство: Springer
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Цена: 46590.00 T
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Описание: This book constitutes the thoroughly refereed post-conference proceedings of the Second International Conference on High Performance Computing in Science and Engineering, HPCSE 2015, held in Solan, Czech Republic, in May 2015. The 14 papers presented in this volume were carefully reviewed and selected from 21 submissions.

High-performance computing on the intel xeon phi

Автор: Wang, Endong Zhang, Qing Shen, Bo Zhang, Guangyong Lu, Xiaowei Wu, Qing Wang, Yajuan
Название: High-performance computing on the intel xeon phi
ISBN: 3319064851 ISBN-13(EAN): 9783319064857
Издательство: Springer
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Цена: 60550.00 T
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Описание: High-Performance Computing on the Intel(R) Xeon Phi`

High Performance Computing

Автор: Carlos Jaime Barrios Hern?ndez; Isidoro Gitler; Ja
Название: High Performance Computing
ISBN: 3319579711 ISBN-13(EAN): 9783319579719
Издательство: Springer
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Цена: 74530.00 T
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Описание: This book constitutes the proceedings of the Third Latin American Conference on High Performance Computing, CARLA 2016, held in Mexico City, Mexico, in August/September 2016.The 30 papers presented in this volume were carefully reviewed and selected from 70 submissions.

Conquering Big Data with High Performance Computing

Автор: Arora
Название: Conquering Big Data with High Performance Computing
ISBN: 3319337408 ISBN-13(EAN): 9783319337401
Издательство: Springer
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Цена: 149060.00 T
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Описание:

This book provides an overview of the resources and research projects that are bringing Big Data and High Performance Computing (HPC) on converging tracks. It demystifies Big Data and HPC for the reader by covering the primary resources, middleware, applications, and tools that enable the usage of HPC platforms for Big Data management and processing.
Through interesting use-cases from traditional and non-traditional HPC domains, the book highlights the most critical challenges related to Big Data processing and management, and shows ways to mitigate them using HPC resources. Unlike most books on Big Data, it covers a variety of alternatives to Hadoop, and explains the differences between HPC platforms and Hadoop.
Written by professionals and researchers in a range of departments and fields, this book is designed for anyone studying Big Data and its future directions. Those studying HPC will also find the content valuable.


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