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Journal of Big Data

, 2:9

First Online: 26 November 2014Received: 30 September 2014Accepted: 06 November 2014


Molecular Simulation MS is a powerful tool for studying physical-chemical features of large systems and has seen applications in many scientific and engineering domains. During the simulation process, the experiments generate a very large number of atoms and intend to observe their spatial and temporal relationships for scientific analysis. The sheer data volumes and their intensive interactions impose significant challenges for data accessing, managing, and analysis. To date, existing MS software systems fall short on storage and handling of MS data, mainly because of the missing of a platform to support applications that involve intensive data access and analytical process. In this paper, we present the database-centric molecular simulation DCMS system our team developed in the past few years. The main idea behind DCMS is to store MS data in a relational database management system DBMS to take advantage of the declarative query interface i.e., SQL, data access methods, query processing, and optimization mechanisms of modern DBMSs. A unique challenge is to handle the analytical queries that are often compute-intensive. For that, we developed novel indexing and query processing strategies including algorithms running on modern co-processors as integrated components of the DBMS. As a result, researchers can upload and analyze their data using efficient functions implemented inside the DBMS. Index structures are generated to store analysis results that may be interesting to other users, so that the results are readily available without duplicating the analysis. We have developed a prototype of DCMS based on the PostgreSQL system and experiments using real MS data and workload show that DCMS significantly outperforms existing MS software systems. We also used it as a platform to test other data management issues such as security and compression.

KeywordsScientific database Molecular simulation Molecular dynamics Data compression Spatiotemporal database Electronic supplementary materialThe online version of this article doi:10.1186-s40537-014-0009-5 contains supplementary material, which is available to authorized users.

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Autor: Anand Kumar - Vladimir Grupcev - Meryem Berrada - Joseph C Fogarty - Yi-Cheng Tu - Xingquan Zhu - Sagar A Pandit - Yuni 

Fuente: https://link.springer.com/

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