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2000
IEEE

Data management for large-scale scientific computations in high performance distributed systems

10 years 2 months ago
Data management for large-scale scientific computations in high performance distributed systems
With the increasing number of scientific applications manipulating huge amounts of data, effective high-level data management is an increasingly important problem. Unfortunately, so far the solutions to the high-level data management problem either require deep understanding of specific storage architectures and file layouts (as in high-performance file storage systems) or produce unsatisfactory I/O performance in exchange for ease-of-use and portability (as in relational DBMSs). In this paper we present a novel application development environment which is built around an active meta-data management system (MDMS) to handle high-level data in an effective manner. The key components of our three-tiered architecture are user application, the MDMS, and a hierarchical storage system (HSS). Our environment overcomes the performance problems of pure database-oriented solutions, while maintaining their advantages in terms of ease-of-use and portability. The high levels of performance are achi...
Alok N. Choudhary, Mahmut T. Kandemir, Jaechun No,
Added 17 Dec 2010
Updated 17 Dec 2010
Type Journal
Year 2000
Where CLUSTER
Authors Alok N. Choudhary, Mahmut T. Kandemir, Jaechun No, Gokhan Memik, Xiaohui Shen, Wei-keng Liao, Harsha S. Nagesh, Sachin More, Valerie E. Taylor, Rajeev Thakur, Rick L. Stevens
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