@InProceedings{choudhary:management, author = {A. Choudhary and M. Kandemir and H. Nagesh and J. No and X. Shen and V. Taylor and S. More and R. Thakur}, title = {Data Management for Large-Scale Scientific Computations in High Performance Distributed Systems}, booktitle = {Proceedings of the Eighth IEEE International Symposium on High Performance Distributed Computing}, year = {1999}, month = {August}, pages = {263--272}, publisher = {IEEE Computer Society Press}, address = {Redondo Beach, CA}, later = {choudhary:jmanagement}, URL = {http://computer.org/conferen/proceed/hpdc/0287/02870042abs.htm}, keywords = {cluster computing, scientific computing, parallel I/O, data management, pario-bib}, abstract = {With the increasing number of scientific applications manipulating huge amounts of data, effective data management is an increasingly important problem. Unfortunately, so far the solutions to this data management problem either require deep understanding of specific storage architectures and file layouts (as in high-performance file systems) or produce unsatisfactory I/O performance in exchange for ease-of-use and portability (as in relational DBMSs).\par In this paper we present a new environment which is built around an active meta-data management system (MDMS). 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.\par The high levels of performance are achieved by the MDMS, with the aid of user-specified directives. Our environment supports a simple, easy-to-use yet powerful user interface, leaving the task of choosing appropriate I/O techniques to the MDMS. We discuss the importance of an active MDMS and show how the three components, namely application, the MDMS, and the HSS, fit together. We also report performance numbers from our initial implementation and illustrate that significant improvements are made possible without undue programming effort.}, comment = {They argue that existing parallel file systems are too low-level, they have their own set of I/O calls (non-portable), and policies are generally hard-coded into the system. Databases provide a portable layer on top of the file system, but they cannot provide high performance. They propose to "combine the advantages of file systems and databases, while avoiding their respective disadvantages." Their system is composed of a user program, a meta-data management system (MDMS), and a heirarchical storage system (HSS). The user program will query the MDMS to learn where in the HSS their data reside, what the performance of the storage system is, information about the acc data from the storage system, etc...} }