Name
Abstract | ||
|---|---|---|
The ability to effectively use computational grids for data intensive applications is becoming increasingly important. The distributed, heterogeneous, shared nature of the computing resources provides a significant challenge in developing support for computationally demanding applications. In this paper we describe several performance optimization techniques we have developed for the filter-stream programming framework that we have designed and implemented for programming data intensive applications on the Grid. We present performance results for multiple versions of a medical imaging application on various distributed machine configurations that show the benefits of the optimizations, and also provide evidence that filter-stream programming can be implemented to both efficiently utilize available Grid resources and to provide scalable application performance as additional resources are made available. |
Year | DOI | Venue |
|---|---|---|
2001 | 10.1109/AMS.2001.993725 | Active Middleware Services |
DocType | ISBN | Citations |
Conference | 0-7695-1528-2 | 12 |
PageRank | References | Authors |
0.81 | 3 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michael D. Beynon | 1 | 441 | 48.83 |
| Alan Sussman | 2 | 1211 | 174.52 |
| Ümit Çatalyürek | 3 | 62 | 4.05 |
| Tahsin Kure | 4 | 12 | 0.81 |
| Joel Saltz | 5 | 44 | 2.82 |