Floating Point Fault Tolerance with Backward Error Assertions
IEEE Transactions on Computers - Special issue on fault-tolerant computing
The grid
Design and implementations of Ninf: towards a global computing infrastructure
Future Generation Computer Systems - Special issue on metacomputing
Future Generation Computer Systems - Special issue on metacomputing
Condor-G: A Computation Management Agent for Multi-Institutional Grids
Cluster Computing
Applying NetSolve's Network-Enabled Server
IEEE Computational Science & Engineering
An end-to-end approach to globally scalable network storage
Proceedings of the 2002 conference on Applications, technologies, architectures, and protocols for computer communications
Mobile Management of Network Files
AMS '01 Proceedings of the Third Annual International Workshop on Active Middleware Services
An end-to-end approach to globally scalable programmable networking
FDNA '03 Proceedings of the ACM SIGCOMM workshop on Future directions in network architecture
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
The Anatomy of the Grid: Enabling Scalable Virtual Organizations
International Journal of High Performance Computing Applications
MapReduce: simplified data processing on large clusters
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Algorithm-Based Fault Tolerance for Matrix Operations
IEEE Transactions on Computers
OSDI'08 Proceedings of the 8th USENIX conference on Operating systems design and implementation
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The persistent mood of exhilaration in the research community over exponential increases in the capacity of computational resources has been tempered recently by the realization that a torrential influx of data from instruments, sensors and simulations is growing even faster than the resources needed to analyze it. The impact of this "data deluge," challenging enough by itself, is exacerbated by the fact that many data intensive projects today involve teams of collaborators spread out across geographically and organizationally distinct sites. A system that addresses these conditions must enable a community of collaborators, distributed throughout the wide area, to get responsive answers to dynamic queries and analyses applied to terascale or larger data sets. In this paper we describe the NetSolve/D system architecture which is designed to achieve this goal of data intensive on-line computing.