@inproceedings{3561a6e66a3b400ba9d4f53940cca4d7,
title = "A model for optimizing file access patterns using spatio-temporal parallelism",
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.",
keywords = "Data analysis, I/O, Modeling, Parallel techniques, Visualization",
author = "Boonthanome Nouanesengsy and John Patchett and James Ahrens and Andrew Bauer and Aashish Chaudhary and Ross Miller and Berk Geveci and Shipman, {Galen M.} and Williams, {Dean N.}",
year = "2013",
doi = "10.1145/2535571.2535593",
language = "English",
isbn = "9781450325004",
series = "Proc. of UltraVis 2013: 8th Int. Workshop on Ultrascale Visualization - Held in Conjunction with SC 2013: The Int. Conference for High Performance Computing, Networking, Storage and Analysis",
booktitle = "Proc. of UltraVis 2013",
note = "8th International Workshop on Ultrascale Visualization, UltraVis 2013 - Held in Conjunction with the International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2013 ; Conference date: 17-11-2013 Through 17-11-2013",
}