Quantify the Effect of Histogram Intersection in Spatio-Temporal Data Sampling
DescriptionThe computational advance in high-performance computing leads to increased data generation by applications, resulting in a bottleneck within the system due to I/O limitations. One solution is the Spatio-temporal sampling method, which takes advantage of both spatial and temporal data reduction methods to produce higher post-reconstruction quality. Various user input parameters such as the number of bins or histogram intersection limit the performance for Spatio-temporal sampling. This poster focuses on determining the effect of the histogram intersection threshold in the Spatio-temporal sampling method. Results indicate that as long as a data set is not identical across adjacent time-steps, reducing the histogram intersection percentage increases the sampling bandwidth until blocks reused become static. The ExaAM data set shows an increase of 100-130% in sampling bandwidth, with only about a 5% decrease in PSNR value at 60% histogram intersection or lower.
Event Type
ACM Student Research Competition: Graduate Poster
ACM Student Research Competition: Undergraduate Poster
Posters
TimeThursday, 17 November 20228:30am - 5pm CST
LocationC1-2-3
TP
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