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LLSuperCloud: Sharing HPC systems for diverse rapid prototyping

Albert Reuther, Jeremy Kepner, William Arcand, David Bestor, Bill Bergeron, Chansup Byun, Matthew Hubbell, Peter Michaleas, Julie Mullen, Andrew Prout, Antonio Rosa
2013 2013 IEEE High Performance Extreme Computing Conference (HPEC)  
The benefits of LLSuperCloud are highlighted using a mixed workload of C MPI, parallel Matlab, Java, databases, and virtualized web services.  ...  Within enterprise computing, commodity computing servers have resulted in the development of a wide range of new cloud capabilities: elastic computing, virtualization, and data hosting.  ...  SUMMARY AND FUTURE WORK This article has explained how a variety of different prototyping job types are being accommodated on the LLGrid shared HPC cluster computing system.  ... 
doi:10.1109/hpec.2013.6670329 dblp:conf/hpec/ReutherKABBBHMMPR13 fatcat:7iw2de4brvfbjdlgm3j7m34bvq

Study of next-generation infrastructure: InfiniBand HPC grid computing for telecommunications data center

Gyankamal Chhajed, Santosh Shinde, Rahul Jagtap, Venkatesh Raskotwar
2010 2010 3rd International Conference on Computer Science and Information Technology  
Grid computing is increasingly being viewed as the next phase of distributed computing.  ...  Grid computing originates in e-Science and its early development was driven to a large extent by the requirements of large-scale computing and efficient sharing of huge datasets. e-Business requirements  ...  The company realized that its traditional SMP infrastructure and enterprise-class Fibre Channel storage area networks (SAN) in operation for nearly a decade-were insufficient to accommodate future demands  ... 
doi:10.1109/iccsit.2010.5564782 fatcat:oauugkslzfgsdlu2yzhjn4drde

pipsCloud: High performance cloud computing for remote sensing big data management and processing

Lizhe Wang, Yan Ma, Jining Yan, Victor Chang, Albert Y. Zomaya
2018 Future generations computer systems  
To solve the aforementioned issues efficiently, we propose pipsCloud which combine recent Cloud computing and HPC techniques to enable large-scale RS data processing system as on-demand real-time services  ...  Benefiting from the ubiquity, elasticity and high-level of transparency of Cloud computing model, the massive RS data managing and data processing for dynamic environmental monitoring are all encapsulate  ...  Following this way, not only VMs but also BMs could be accommodated for on-demand needs of variable HPC cluster platform for RS applications, so as to decrease performance penalty.  ... 
doi:10.1016/j.future.2016.06.009 fatcat:gnkwaeggozcenkbuw7vdbmhe7i

An Autonomic Approach to Integrated HPC Grid and Cloud Usage

Hyunjoo Kim, Yaakoub el-Khamra, Shantenu Jha, Manish Parashar
2009 2009 Fifth IEEE International Conference on e-Science  
The primary goal of this paper is to experimentally investigate, from an applications perspective, how autonomics can enable interesting usage modes and scenarios for integrating HPC Grid and Clouds.  ...  Clouds are rapidly joining high-performance Grids as viable computational platforms for scienti c exploration and discovery, and it is clear that production computational infrastructures will integrate  ...  research presented in this paper is supported in part by National Science Foundation via grants numbers IIP 0758566, CCF-0833039, DMS-0835436, CNS 0426354, IIS 0430826, and CNS 0723594, by Department of  ... 
doi:10.1109/e-science.2009.58 dblp:conf/eScience/KimKJP09 fatcat:swbuj3ohvrbcloa5ccp6b6myjq

High Performance Computing and Industry 4.0: Experiences from the DISRUPT Project

Rizos Sakellariou, Jorge Buenabad-Chávez, Evangelia Kavakli, Ilias Spais, Vasilios Tountopoulos
2018 Zenodo  
and the factories of the future.  ...  This vision, commonly termed as Industry 4.0, is at the core of a number of funded projects in Europe.  ...  HPC on demand: The concept of 'HPC on demand' has long been associated with dynamic adjustment of resources for compute and visualization workloads (often through cloud infrastructures) or, additionally  ... 
doi:10.5281/zenodo.3528266 fatcat:456nrt6mvbfpzezbuzxddoqgy4

Supercomputing Centers and Electricity Service Providers: A Geographically Distributed Perspective on Demand Management in Europe and the United States [chapter]

Tapasya Patki, Natalie Bates, Girish Ghatikar, Anders Clausen, Sonja Klingert, Ghaleb Abdulla, Mehdi Sheikhalishahi
2016 Lecture Notes in Computer Science  
grid operation.  ...  In this paper, we first present results from a detailed, quantitative survey-based analysis and compare the perspectives of the European grid and SCs to the ones of the United States (US).  ...  ESPs today already face reliability concerns for accommodating megawatt-level fluctuations from SCs and often require HPC client sites to forecast their electricity use.  ... 
doi:10.1007/978-3-319-41321-1_13 fatcat:7jokoczys5fwjia5t7d6hpxmfi

Dynamic Distribution of High-Rate Data Processing from CERN to Remote HPC Data Centers

T. Boccali, D. Cameron, N. Cardo, D. Conciatore, A. Di Girolamo, G. Dissertori, P. Fernandez, A. Filipcic, M. Gila, C. Grab, J. Elmsheuser, V. Jankauskas (+9 others)
2021 Computing and Software for Big Science  
computer site as on demand extension of the CERN Tier-0, which could play a role in addressing the future LHC computing challenges for the high luminosity LHC.  ...  This is implemented using containers, tuning the existing batch scheduler and reinforcing the scratch file system, while still using standard Grid middleware.  ...  Since CERN Tier-0 workloads have never been run on a high performance computer (HPC), we aim at tackling all the technical challenges posed by such demanding workloads.  ... 
doi:10.1007/s41781-020-00052-w fatcat:xjkjc7ps5ncvhkvvjnv6d2svni

Granular Security for a Science Gateway in Structural Bioinformatics

Sandra Gesing, Richard Grunzke, Ákos Balaskó, Georg Birkenheuer, Dirk Blunk, Sebastian Breuers, André Brinkmann, Gregor Fels, Sonja Herres-Pawlis, Péter Kacsuk, Miklos Kozlovszky, Jens Krüger (+9 others)
2011 International Workshop on Science Gateways  
HPC facilities.  ...  It ensures the confidentiality, integrity and availability of data via a granular security concept which covers all layers of the infrastructure.  ...  ACKNOWLEDGEMENT We would like to thank Valentina Huber for the basic version of the applet for generating SAML assertions.  ... 
dblp:conf/iwsg/GesingGBBBBBFHKK0PSSSSFWMK11 fatcat:t3aqeypi5zh3haaobqq7g4ppsm

PanDA: Exascale Federation of Resources for the ATLAS Experiment at the LHC

Fernando Barreiro Megino, Jose Caballero Bejar, Kaushik De, John Hover, Alexei Klimentov, Tadashi Maeno, Paul Nilsson, Danila Oleynik, Siarhei Padolski, Sergey Panitkin, Artem Petrosyan, Torre Wenaus (+3 others)
2016 EPJ Web of Conferences  
Given diverse funding constraints, the computational resources for the LHC have been deployed in a worldwide mesh of data centres, connected to each other through Grid technologies.  ...  Since its origins, PanDA has evolved together with upcoming computing paradigms in and outside HEP, such as changes in the networking model, Cloud Computing and HPC.  ...  Department of Energy, Office of Science, High Energy Physics and ASCR Contract No. DE-AC02-98CH10886 and Contract No.  ... 
doi:10.1051/epjconf/201610801001 fatcat:4ybnlkphxrf3jayexd4mljmr4m

A survey on resource allocation in high performance distributed computing systems

Hameed Hussain, Saif Ur Rehman Malik, Abdul Hameed, Samee Ullah Khan, Gage Bickler, Nasro Min-Allah, Muhammad Bilal Qureshi, Limin Zhang, Wang Yongji, Nasir Ghani, Joanna Kolodziej, Albert Y. Zomaya (+11 others)
2013 Parallel Computing  
Moreover, we have classified the HPC systems into three broad categories, namely: (a) cluster, (b) grid, and (c) cloud systems and define the characteristics of each class by extracting sets of common  ...  Therefore, a comprehensive discussion of widely used resource allocation strategies deployed in HPC environment is required, which is one of the motivations of this survey.  ...  Department of Energy Office of Science laboratory, is operated under Contract No. DE-AC02-06CH11357. The U.S.  ... 
doi:10.1016/j.parco.2013.09.009 fatcat:pdbghbohinc55lsgv67yfiw5ni

Hardware-Assisted Detection of Firmware Attacks in Inverter-Based Cyberphysical Microgrids [article]

Abraham Peedikayil Kuruvila, Ioannis Zografopoulos, Kanad Basu, Charalambos Konstantinou
2021 arXiv   pre-print
The electric grid modernization effort relies on the extensive deployment of microgrid (MG) systems.  ...  The proposed HPCs measure periodically the order of various instruction types within the MG inverter's firmware code.  ...  Different inverters exist in order to accommodate the field application requirements of grid systems [29] , [30] .  ... 
arXiv:2009.07691v2 fatcat:fuw6e5bdkrdnfpl4ca4ginp3k4

Big Data Analytics for Dynamic Energy Management in Smart Grids

Panagiotis D. Diamantoulakis, Vasileios M. Kapinas, George K. Karagiannidis
2015 Big Data Research  
The most important challenge in a smart grid (SG) is how to take advantage of the users' participation in order to reduce the cost of power.  ...  The smart electricity grid enables a two-way flow of power and data between suppliers and consumers in order to facilitate the power flow optimization in terms of economic efficiency, reliability and sustainability  ...  Acknowledgement This work was supported by the project of "Scalable Real-Time Load Forecasting in Smart Grid" under a grant from the Khalifa University Internal Research Fund (KUIRF-Level 2; Fund # 210063  ... 
doi:10.1016/j.bdr.2015.03.003 fatcat:2rz5wct5djfjhcec6xic5rnd3i


Kitty Ahuja .
2014 International Journal of Research in Engineering and Technology  
The goal of HPC is to reduce execution time and accommodate larger and more complicated problems.  ...  The scope of HPC is scientific research and engineering as well as the design of enterprise applications.  ...  Meanwhile, SGI unveiled on demand cloud HPC service called Cyclone in 2010 [13] .  ... 
doi:10.15623/ijret.2014.0301070 fatcat:xxctnysnmfbsrlbgqq52ij7xp4

Scheduler technologies in support of high performance data analysis

Albert Reuther, Chansup Byun, William Arcand, David Bestor, Bill Bergeron, Matthew Hubbell, Michael Jones, Peter Michaleas, Andrew Prout, Antonio Rosa, Jeremy Kepner
2016 2016 IEEE High Performance Extreme Computing Conference (HPEC)  
This paper compares and contrasts the features of HPC and Big Data schedulers with a focus on accommodating both scientific computing and high performance data analytic workloads.  ...  Grid Engine, Mesos, and Yarn.  ...  Feature LSF Grid Engine Slurm YARN Mesos Kubernetes Type HPC HPC HPC Big Data Big Data Big Data Cost/Licensing $$$ $$$, Open source Open source Open source Open source Open source  ... 
doi:10.1109/hpec.2016.7761604 dblp:conf/hpec/ReutherBABBHJMP16 fatcat:7npyzy32dzhqhl65soe6qpadpq

The ATLAS Event Service: A new approach to event processing

P Calafiura, K De, W Guan, T Maeno, P Nilsson, D Oleynik, S Panitkin, V Tsulaia, P Van Gemmeren, T Wenaus
2015 Journal of Physics, Conference Series  
Department of Energy, Office of Science, High Energy Physics.  ...  A specialization of the Event Service for HPCs, Yoda [13] , was developed to accommodate the particular features of HPC architectures, most notably the lack of outbound access from worker nodes.  ...  The system is close to entering production on HPC, commercial cloud, grid and volunteer computing platforms.  ... 
doi:10.1088/1742-6596/664/6/062065 fatcat:tzaig3bawbaefjwbi7tplb566m
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