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.

Simulating Sonic Scanner responses in an interactive Web‐based High Performance Computing environment

2008 ◽  
Vol 123 (5) ◽  
pp. 3373-3373
Author(s):  
Valery Polyakov ◽  
Henri‐Pierre Valero ◽  
Dzevat Omeragic ◽  
Raymond L. Kocian ◽  
Tarek M. Habashy ◽  
...  
Keyword(s):  
High Performance Computing ◽  
High Performance ◽  
Computing Environment ◽  
Web Based ◽  
Performance Computing

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 environment: a review of twenty years of experiments in China

2016 ◽  
Vol 3 (1) ◽  
pp. 36-48 ◽  
Author(s):  
Zhiwei Xu ◽  
Xuebin Chi ◽  
Nong Xiao
Keyword(s):  
High Performance Computing ◽  
High Performance ◽  
The Internet ◽  
Computing Environment ◽  
Open Problems ◽  
Loosely Coupled ◽  
The Past ◽  
Important Open Problem ◽  
Computing Environments ◽  
Performance Computing

Abstract A high-performance computing environment, also known as a supercomputing environment, e-Science environment or cyberinfrastructure, is a crucial system that connects users’ applications to supercomputers, and provides usability, efficiency, sharing, and collaboration capabilities. This review presents important lessons drawn from China's nationwide efforts to build and use a high-performance computing environment over the past 20 years (1995–2015), including three observations and two open problems. We present evidence that such an environment helps to grow China's nationwide supercomputing ecosystem by orders of magnitude, where a loosely coupled architecture accommodates diversity. An important open problem is why technology for global networked supercomputing has not yet become as widespread as the Internet or Web. In the next 20 years, high-performance computing environments will need to provide zettaflops computing capability and 10 000 times better energy efficiency, and support seamless human-cyber-physical ternary computing.

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