Redirigiendo al acceso original de articulo en 16 segundos...
ARTÍCULO
TITULO

Long Distance Geographically Distributed InfiniBand Based Computing

Karol Niedzielewski    
Marcin Semeniuk    
Jaroslaw Skomial    
Jerzy Proficz    
Piotr Sumioka    
Bartosz Pliszka    
Marek Michalewicz    

Resumen

Collaboration between multiple computing centres, referred as federated computing is becoming important pillar of High Performance Computing (HPC) and will be one of its key components in the future. To test technical possibilities of future collaboration using 100Gb optic fiber link (Connection was 900 km in length with 9ms RTT time) we prepared two scenarios of operation.In the first one, Interdisciplinary Centre for Mathematical and Computational Modelling (ICM) in Warsaw and Centre of Informatics - Tricity Academic Supercomputer & networK (CI-TASK) in Gdansk prepared a long distance geographically distributed computing cluster. System consisted of 14 nodes (10 nodes at ICM facility and 4 at TASK facility) connected using InfiniBand. Our tests demonstrate that it is possible to perform computationally intensive data analysis on systems of this class without substantial drop in performance for a certain type of workloads. Additionally, we show that it is feasible to use High Performance Parallex [1], high level abstraction libraries for distributed computing, to develop software for such geographically distributed computing resources and maintain desired efficiency.In the second scenario, we prepared distributed simulation-postprocessing-visualization workflow using ADIOS2 [2] and two programming languages (C++ and python). In this test we prove capabilities of performing different parts of analysis in seperate sites.

 Artículos similares

       
 
François Legrand, Richard Macwan, Alain Lalande, Lisa Métairie and Thomas Decourselle    
Automated Cardiac Magnetic Resonance segmentation serves as a crucial tool for the evaluation of cardiac function, facilitating faster clinical assessments that prove advantageous for both practitioners and patients alike. Recent studies have predominant... ver más
Revista: Algorithms

 
Marco Battaglieri, Andrea Bianconi, Mariangela Bondí, Raffaella De Vita, Antonino Fulci, Giulia Gosta, Stefano Grazzi, Hyon-Suk Jo, Changhui Lee, Giuseppe Mandaglio, Valerio Mascagna, Tetiana Nagorna, Alessandro Pilloni, Marco Spreafico, Luca J. Tagliapietra, Luca Venturelli and Tommaso Vittorini    
The interaction of a high-current O(100 µA), medium energy O(10 GeV) electron beam with a thick target O(1m) produces an overwhelming shower of standard model particles in addition to hypothetical light dark matter particles. While most of the radiation ... ver más
Revista: Instruments

 
Lígia Conceição, Gonçalo Homem de Almeida Correia, Bart van Arem and José Pedro Tavares    
Once trusted, automated vehicles (AVs) will gradually appear in urban areas. Such a transition is an opportunity in transport planning to control undesired impacts and possibly mitigate congestion at a time when both conventional vehicles (CVs) and AVs c... ver más
Revista: Infrastructures

 
Futo Ueda, Hiroto Tanouchi, Nobuyuki Egusa and Takuya Yoshihiro    
River water-level prediction is crucial for mitigating flood damage caused by torrential rainfall. In this paper, we attempt to predict river water levels using a deep learning model based on radar rainfall data instead of data from upstream hydrological... ver más
Revista: Water

 
Changjing Fu, Yangming Xu and Tianlong Zhao    
One of the major geological hazards that can cause harm to long-distance oil and gas pipelines are water-induced disasters. These disasters are quite common and widespread. Pipelines that cross river channels are at a higher risk of facing damage due to ... ver más
Revista: Water