Achieving Portable Performance For Wavelet Compression Using Data Parallel Primitives

Simple item page
dc.contributor.authorLi, Shaomengen_US
dc.contributor.authorMarsaglia, Nicoleen_US
dc.contributor.authorChen, Vincenten_US
dc.contributor.authorSewell, Christopheren_US
dc.contributor.authorClyne, Johnen_US
dc.contributor.authorChilds, Hanken_US
dc.contributor.editorAlexandru Telea and Janine Bennetten_US
dc.date.accessioned2017-06-12T05:12:24Z
dc.date.available2017-06-12T05:12:24Z
dc.date.issued2017
dc.description.abstractWe consider the problem of wavelet compression in the context of portable performance over multiple architectures. We contribute a new implementation of the wavelet transform algorithm that uses data parallel primitives from the VTK-m library. Because of the data parallel primitives approach, our algorithm is hardware-agnostic and yet can run on many-core architectures. We also study the efficacy of this implementation over multiple architectures against hardware-specific comparators. Results show that our performance is portable, scales well, and is comparable to native implementations. Finally, we argue that compression times for large data sets are likely fast enough to fit within in situ constraints, adding to the evidence that wavelet transformation could be an effective in situ compression operator.en_US
dc.description.sectionheadersAlternative Programming Model Techniques
dc.description.seriesinformationEurographics Symposium on Parallel Graphics and Visualization
dc.identifier.doi10.2312/pgv.20171095
dc.identifier.isbn978-3-03868-034-5
dc.identifier.issn1727-348X
dc.identifier.pages73-81
dc.identifier.urihttps://doi.org/10.2312/pgv.20171095
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/pgv20171095
dc.publisherThe Eurographics Associationen_US
dc.titleAchieving Portable Performance For Wavelet Compression Using Data Parallel Primitivesen_US
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
073-081.pdf
Size:
295.05 KB
Format:
Adobe Portable Document Format
Download
Collections
EGPGV17: Eurographics Symposium on Parallel Graphics and Visualization