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OpenSHMEM and Related Technologies. Big Compute and Big Data Convergence

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This book constitutes the proceedings of the 4th OpenSHMEM Workshop, held in Annapolis, MD, USA, in August 2017.The 11 full paper... Weiterlesen
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Beschreibung

This book constitutes the proceedings of the 4th OpenSHMEM Workshop, held in Annapolis, MD, USA, in August 2017.
The 11 full papers presented in this book were carefully reviewed and selected from 14 submissions. The papers discuss a variety of ideas for extending the OpenSHMEM specification and making it efficient for current and next generation systems. This includes new research for communication contexts in OpenSHMEM, different optimizations for OpenSHMEM on shared memory machines, exploring the implementation of OpenSHMEM and its memory model on Intel's KNL architecture, and implementing new applications and benchmarks with OpenSHMEM.



Inhalt

Symmetric Memory Partitions in OpenSHMEM: A Case Study with Intel KNL.- Implementation and Evaluation of OpenSHMEM Contexts Using OFI Libfabric.- Merged Requests for Better Performance and Productivity in Multithreaded OpenSHMEM.- Evaluating Contexts in OpenSHMEM-X Reference Implementation.- Parallelizing Single Source Shortest Path with OpenSHMEM.- Efficient Breadth First Search on Multi-GPU Systems Using GPU-centric OpenSHMEM.- Application-Level Optimization of On-Node Communication in OpenSHMEM.- SHMEMCache with MPI One-Sided Operation.- Balancing Performance and Portability with Containers in HPC: An OpenSHMEM Example.- Exploiting and Evaluating OpenSHMEM on KNL Architecture.- Performance Analysis of OpenSHMEM Applications with TAU Commander.

Produktinformationen

Titel: OpenSHMEM and Related Technologies. Big Compute and Big Data Convergence
Untertitel: 4th Workshop, OpenSHMEM 2017, Annapolis, MD, USA, August 7-9, 2017, Revised Selected Papers
Editor:
EAN: 9783319738147
Digitaler Kopierschutz: Wasserzeichen
Format: E-Book (pdf)
Hersteller: Springer International Publishing
Genre: IT & Internet
Anzahl Seiten: 181
Veröffentlichung: 25.01.2018
Dateigrösse: 21.7 MB

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