Name
Abstract | ||
|---|---|---|
For many years now, I/O read time has been recognized as the primary bottleneck for parallel visualization and analysis of large-scale data. In this paper, we introduce a model that can estimate the read time for a file stored in a parallel filesystem when given the file access pattern. Read times ultimately depend on how the file is stored and the access pattern used to read the file. The file access pattern will be dictated by the type of parallel decomposition used. We employ spatio-temporal parallelism, which combines both spatial and temporal parallelism, to provide greater flexibility to possible file access patterns. Using our model, we were able to configure the spatio-temporal parallelism to design optimized read access patterns that resulted in a speedup factor of approximately 400 over traditional file access patterns. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1145/2535571.2535593 | UltraVis@SC |
Field | DocType | Citations |
File Control Block,Stub file,Self-certifying File System,Computer science,Parallel computing,Unix file types,Fork (file system),Versioning file system,File system fragmentation,Computer file | Conference | 0 |
PageRank | References | Authors |
0.34 | 15 | 9 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Boonthanome Nouanesengsy | 1 | 92 | 4.78 |
| John Patchett | 2 | 71 | 6.20 |
| James P. Ahrens | 3 | 290 | 23.19 |
| Andrew C. Bauer | 4 | 130 | 7.21 |
| Aashish Chaudhary | 5 | 0 | 0.68 |
| Ross Miller | 6 | 33 | 2.89 |
| Berk Geveci | 7 | 277 | 20.83 |
| Galen M. Shipman | 8 | 299 | 22.83 |
| Dean N. Williams | 9 | 104 | 11.36 |