Building a scientific data grid with D i GS

2009 ◽  
Vol 367 (1897) ◽  
pp. 2471-2481 ◽  
Author(s):  
Mark G. Beckett ◽  
Chris R. Allton ◽  
Christine T.H. Davies ◽  
Ilan Davis ◽  
Jonathan M. Flynn ◽  
...  
Keyword(s):  
Molecular Biology ◽  
High Performance Computing ◽  
Particle Physics ◽  
High Performance ◽  
Scientific Data ◽  
Grid Technology ◽  
Data Infrastructure ◽  
Software Application ◽  
Performance Computing ◽  
Insight Into

We provide an insight into the challenge of building and supporting a scientific data infrastructure with reference to our experience working with scientists from computational particle physics and molecular biology. We illustrate how, with modern high-performance computing resources, even small scientific groups can generate huge volumes (petabytes) of valuable scientific data and explain how grid technology can be used to manage, publish, share and curate these data. We describe the D i GS software application, which we have developed to meet the needs of smaller communities and we have highlighted the key elements of its functionality.

scholarly journals High-Performance Computing of BEAST/BEAGLE in Bayesian Phylogenetics using SDumont Hybrid Resources

2020 ◽  
Author(s):  
Kary Ocaña ◽  
Micaella Coelho ◽  
Guilherme Freire ◽  
Carla Osthoff
Keyword(s):  
High Performance Computing ◽  
High Performance ◽  
Current Knowledge ◽  
Data Sets ◽  
Length Estimation ◽  
Computationally Intensive ◽  
Mcmc Chain ◽  
Performance Computing ◽  
Insight Into

Bayesian phylogenetic algorithms are computationally intensive. BEAST 1.10 inferences made use of the BEAGLE 3 high-performance library for efficient likelihood computations. The strategy allows phylogenetic inference and dating in current knowledge for SARS-CoV-2 transmission. Follow-up simulations on hybrid resources of Santos Dumont supercomputer using four phylogenomic data sets, we characterize the scaling performance behavior of BEAST 1.10. Our results provide insight into the species tree and MCMC chain length estimation, identifying preferable requirements to improve the use of high-performance computing resources. Ongoing steps involve analyzes of SARS-CoV-2 using BEAST 1.8 in multi-GPUs.

scholarly journals Testing the Scalability of the HS-AUTOFIT Tool in a High-Performance Computing Environment

Electronics ◽  
2021 ◽  
Vol 10 (18) ◽  
pp. 2251
Author(s):  
Giuseppe Di Modica ◽  
Luca Evangelisti ◽  
Luca Foschini ◽  
Assimo Maris ◽  
Sonia Melandri
Keyword(s):  
High Performance Computing ◽  
High Performance ◽  
Computing Time ◽  
Rotational Spectroscopy ◽  
Computing Environment ◽  
Computing Power ◽  
Chirped Pulse ◽  
Software Application ◽  
Performance Computing ◽  
Short Times

In the last years, the development of broadband chirped-pulse Fourier transform microwave spectrometers has revolutionized the field of rotational spectroscopy. Currently, it is possible to experimentally obtain a large quantity of spectra that would be difficult to analyze manually due to two main reasons. First, recent instruments allow obtaining a considerable amount of data in very short times, and second, it is possible to analyze complex mixtures of molecules that all contribute to the density of the spectra. AUTOFIT is a spectral assignment software application that was developed in 2013 to support and facilitate the analysis. Notwithstanding the benefits AUTOFIT brings in terms of automation of the analysis of the accumulated data, it still does not guarantee a good performance in terms of execution time because it leverages the computing power of a single computing machine. To cater to this requirement, we developed a parallel version of AUTOFIT, called HS-AUTOFIT, capable of running on high-performance computing (HPC) clusters to shorten the time to explore and analyze spectral big data. In this paper, we report some tests conducted on a real HPC cluster aimed at providing a quantitative assessment of HS-AUTOFIT’s scaling capabilities in a multi-node computing context. The collected results demonstrate the benefits of the proposed approach in terms of a significant reduction in computing time.

scholarly journals EUDAT: A New Cross-Disciplinary Data Infrastructure for Science

2013 ◽  
Vol 8 (1) ◽  
pp. 279-287 ◽  
Author(s):  
Damien Lecarpentier ◽  
Peter Wittenburg ◽  
Willem Elbers ◽  
Alberto Michelini ◽  
Riam Kanso ◽  
...  
Keyword(s):  
High Performance Computing ◽  
High Performance ◽  
Research Data ◽  
Shared Services ◽  
National Data ◽  
Data Infrastructure ◽  
European Data ◽  
Funding Agencies ◽  
Performance Computing ◽  
Cross National

The EUDAT project is a pan-European data initiative that started in October 2011. The project brings together a unique consortium of 25 partners – including research communities, national data and high performance computing (HPC) centres, technology providers, and funding agencies – from 13 countries. EUDAT aims to build a sustainable cross-disciplinary and cross-national data infrastructure that provides a set of shared services for accessing and preserving research data.

scholarly journals Tools and Services for High Performance Computing

2017 ◽  
Vol 17 (5) ◽  
pp. 81-88
Author(s):  
Dimitar Dimitrov ◽  
Emanouil Atanassov
Keyword(s):  
High Performance Computing ◽  
High Performance ◽  
User Authentication ◽  
Service Architecture ◽  
Accounting Data ◽  
Data Infrastructure ◽  
Usage Patterns ◽  
Authentication And Authorization ◽  
And Storage ◽  
Performance Computing

Abstract The accounting platform is a web-service based system for collection and analysis of accounting data from different infrastructure resources like High Performance Computing (HPC), Cloud and storage systems. The platform has two major components - backend API services along with different data publishers and a client web UI module for visualization and operations. The backend API is designed to gather information from different job management systems, cloud vendors, and storage providers and use micro-service architecture. The web UI module is written in Python, JavaScript and has integrated SAML login module for user authentication and authorization. It is capable of visualizing the gathered data in dynamic OLAP style and supports standard export formats like CSV and Excel. Through the accounting platform, it is possible to obtain a full view of the usage patterns of an integrated electronic infrastructure and to see from one point all information about the different resources comprising the hybrid computing and data infrastructure.

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