A Study of Parallel Data Compression Using Proper Orthogonal Decomposition on the K Computer

Simple item page
dc.contributor.authorBi, Chongkeen_US
dc.contributor.authorOno, Kenjien_US
dc.contributor.authorMa, Kwan-Liuen_US
dc.contributor.authorWu, Haiyuanen_US
dc.contributor.authorImamura, Toshiyukien_US
dc.contributor.editorMargarita Amor and Markus Hadwigeren_US
dc.date.accessioned2014-12-16T07:31:15Z
dc.date.available2014-12-16T07:31:15Z
dc.date.issued2014en_US
dc.description.abstractThe growing power of supercomputers continues to improve scientists' ability to model larger, more sophisticated problems in science with higher accuracy. An equally important ability is to make full use of the data output from the simulations to help clarify the modeled phenomena and facilitate the discovery of new phenomena. However, along with the scale of computation, the size of the resulting data has exploded; it becomes infeasible to output most of the data, which defeats the purpose of conducting large-scale simulations. In order to address this issue so that more data may be archived and studied, we have developed a scalable parallel data compression solution to reduce the size of large-scale data with low computational cost and minimal error. We use the proper orthogonal decomposition (POD) method to compress data because this method can effectively extract the main features from the data, and the resulting compressed data can be decompressed in linear time. Our implementation achieves high parallel efficiency with a binary load-distributed approach, which is similar to the binary-swap image composition method. This approach allows us to effectively use all of the processors and to reduce the interprocessor communication cost throughout the parallel compression calculations. The results of tests using the K computer indicate the superior performance of our design and implementationen_US
dc.description.seriesinformationEurographics Symposium on Parallel Graphics and Visualizationen_US
dc.identifier.isbn978-3-905674-59-0en_US
dc.identifier.issn1727-348Xen_US
dc.identifier.urihttps://doi.org/10.2312/pgv.20141078en_US
dc.identifier.urihttps://diglib.eg.org/handle/10.2312/pgv.20141078.001-008
dc.publisherThe Eurographics Associationen_US
dc.subjectCompression [I.4.2]en_US
dc.subjectApproximate methodsen_US
dc.subjecten_US
dc.subjectModes of Computation [F.1.2]en_US
dc.subjectParallelism and concurrencyen_US
dc.titleA Study of Parallel Data Compression Using Proper Orthogonal Decomposition on the K Computeren_US
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
001-008.pdf
Size:
2.66 MB
Format:
Adobe Portable Document Format
Download
Collections
EGPGV14: Eurographics Symposium on Parallel Graphics and Visualization