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Titlebook: High Performance Computing; 4th Latin American C Esteban Mocskos,Sergio Nesmachnow Conference proceedings 2018 The Editor(s) (if applicable

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發(fā)表于 2025-3-21 19:57:42 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱High Performance Computing
副標題4th Latin American C
編輯Esteban Mocskos,Sergio Nesmachnow
視頻videohttp://file.papertrans.cn/427/426294/426294.mp4
概述Includes supplementary material:
叢書名稱Communications in Computer and Information Science
圖書封面Titlebook: High Performance Computing; 4th Latin American C Esteban Mocskos,Sergio Nesmachnow Conference proceedings 2018 The Editor(s) (if applicable
描述.This book constitutes the proceedings of the 4th Latin American Conference on High Performance Computing, CARLA 2017, held in Buenos Aires, Argentina, and Colonia del Sacramento, Uruguay, in September 2017..The 29 papers presented in this volume were carefully reviewed and selected from 50 submissions. They are organized in topical sections named: HPC infrastructures and datacenters;?HPC industry and education;?GPU, multicores, accelerators;?HPC applications and tools;?big data and data management;?parallel and distributed algorithms;?Grid, cloud and federations..
出版日期Conference proceedings 2018
關鍵詞high-performance computing; parallel programming techniques; distributed computation; cluster computing
版次1
doihttps://doi.org/10.1007/978-3-319-73353-1
isbn_softcover978-3-319-73352-4
isbn_ebook978-3-319-73353-1Series ISSN 1865-0929 Series E-ISSN 1865-0937
issn_series 1865-0929
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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Initial Experiences from TUPAC Supercomputerfacilities in a country is an effort that should be carefully used and must be as open as possible to strengthen the impact of these resources..We describe the current status and characteristics of TUPAC supercomputer, which is hosted by a CONICET research institute. Unlike other experiences in Arge
地板
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romeoLAB: A High Performance Training Platform for HPC, GPU and DeepLearningogeneous architectures. The full hybrid cluster . has been used in that purpose since a long time in order to train master students and cluster users. The main issue for trainees is the cost of accessing and exploiting a production facility in a pedagogic context. The use of some specific techniques
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Analysis and Characterization of GPU Benchmarks for Kernel Concurrency Efficiencyed to CPUs. However, programming GPUs requires a different mindset and optimization techniques that take advantage of the peculiarities of the GPU architecture. Moreover, GPUs are rapidly changing, in the sense of including capabilities that can improve performance of general purpose applications, s
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Evaluating the NVIDIA Tegra Processor as a Low-Power Alternative for Sparse GPU Computationsis the necessity to contemplate energy consumption restrictions. As an alternative for reducing the power consumption of large clusters, new systems that include unconventional devices have been proposed. In particular, it is now common to encounter energy-efficient hardware such as GPUs and low-pow
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Benchmarking Performance: Influence of Task Location on Cluster Throughputf parallelism, dedicated computational resources, strong- and weak-scaling behaviour, to cite some). This situation causes scheduling decisions to have a great influence on the performance of the applications, making difficult to achieve an optimal exploitation with cost-effective strategies of the
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PRIMULA: A Framework Based on Finite Elements to Address Multi Scale and Multi Physics Problemserential equations is presented. PRIMULA is portable to LINUX/UNIX, where it is compiled with gfortran, and to WINDOWS, compiled in the Visual Studio environment. It can be compiled to run in series, with shared memory under the Standard OPENMP, in a distributed environment under Standard MPI and on
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