Next Article in Journal
Melatonin Pharmacokinetics Following Oral Administration in Preterm Neonates
Next Article in Special Issue
A Robust Manifold Graph Regularized Nonnegative Matrix Factorization Algorithm for Cancer Gene Clustering
Previous Article in Journal
Multi Component Reactions under Increased Pressure: On the Mechanism of Formation of Pyridazino[5,4,3-de][1,6]naphthyridine Derivatives by the Reaction of Malononitrile, Aldehydes and 2-Oxoglyoxalarylhydrazones in Q-Tubes
Previous Article in Special Issue
Cancer Classification Based on Support Vector Machine Optimized by Particle Swarm Optimization and Artificial Bee Colony
Open AccessArticle

An Interface for Biomedical Big Data Processing on the Tianhe-2 Supercomputer

1
College of Computer, National University of Defense Technology, Changsha 410073, China
2
Beijing Genomics Institute (BGI) Shenzhen, Shenzhen 518083, China
3
National Supercomputing Center of Guangzhou, Guangzhou 510006, China
4
School of Data and Computer Science, Sun Yat-Sen University, Guangzhou 510000, China
*
Authors to whom correspondence should be addressed.
Molecules 2017, 22(12), 2116; https://doi.org/10.3390/molecules22122116
Received: 25 October 2017 / Accepted: 29 November 2017 / Published: 1 December 2017
Big data, cloud computing, and high-performance computing (HPC) are at the verge of convergence. Cloud computing is already playing an active part in big data processing with the help of big data frameworks like Hadoop and Spark. The recent upsurge of high-performance computing in China provides extra possibilities and capacity to address the challenges associated with big data. In this paper, we propose Orion—a big data interface on the Tianhe-2 supercomputer—to enable big data applications to run on Tianhe-2 via a single command or a shell script. Orion supports multiple users, and each user can launch multiple tasks. It minimizes the effort needed to initiate big data applications on the Tianhe-2 supercomputer via automated configuration. Orion follows the “allocate-when-needed” paradigm, and it avoids the idle occupation of computational resources. We tested the utility and performance of Orion using a big genomic dataset and achieved a satisfactory performance on Tianhe-2 with very few modifications to existing applications that were implemented in Hadoop/Spark. In summary, Orion provides a practical and economical interface for big data processing on Tianhe-2. View Full-Text
Keywords: big data; Tianhe-2; Hadoop; Spark; genomics big data big data; Tianhe-2; Hadoop; Spark; genomics big data
Show Figures

Figure 1

MDPI and ACS Style

Yang, X.; Wu, C.; Lu, K.; Fang, L.; Zhang, Y.; Li, S.; Guo, G.; Du, Y. An Interface for Biomedical Big Data Processing on the Tianhe-2 Supercomputer. Molecules 2017, 22, 2116.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop