Fast online predictive compression of radio astronomy data

dc.contributor.authorHugo, Benjamin
dc.date.accessioned2016-08-13T18:45:54Z
dc.date.available2016-08-13T18:45:54Z
dc.date.issued2013
dc.date.updated2016-08-13T18:25:43Z
dc.description.abstractThis report investigates the fast, lossless compression of 32-bit single precision floating-point values. High speed compression is critical in the context of the MeerKAT radio telescope currently under construction in Southern Africa and Australia, which will produce data at rates up to 1 Petabyte every 20 seconds. The compression technique being investigated is based on predictive compression, which has proven successful at achieving high-speed compression in previous research. Several different predictive techniques (which includes polynomial extrapolation), along with CPU- and GPU-based parallelization approaches are discussed. The implementation successfully achieves throughput rates in excess of 6 GiB/s for compression and much higher rates for decompression using a 64-core AMD Opteron machine, achieving file-size reductions of, on average 9%. Furthermore the results of concurrent investigations into block-based parallel Huffman encoding and Zero-length Encoding are compared to the predictive scheme and it was found that the predictive scheme obtains approximately 4%-5% better compression ratios than the Zero-Length Encoder and is 25 times faster than Huffman encoding on an Intel Xeon E5 processor. The scheme may be well-suited to address the large network bandwidth requirements of the MeerKAT project.en_ZA
dc.identifier.apacitationHugo, B. (2013). <i>Fast online predictive compression of radio astronomy data</i>. (ThesesThesis). University of Cape Town ,Unknown ,Computer Science. Retrieved from http://hdl.handle.net/11427/21225en_ZA
dc.identifier.chicagocitationHugo, Benjamin. <i>"Fast online predictive compression of radio astronomy data."</i> ThesesThesis., University of Cape Town ,Unknown ,Computer Science, 2013. http://hdl.handle.net/11427/21225en_ZA
dc.identifier.citationHugo, H. 2013. Fast online predictive compression of radio astronomy data. Honours Thesis. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Hugo, Benjamin AB - This report investigates the fast, lossless compression of 32-bit single precision floating-point values. High speed compression is critical in the context of the MeerKAT radio telescope currently under construction in Southern Africa and Australia, which will produce data at rates up to 1 Petabyte every 20 seconds. The compression technique being investigated is based on predictive compression, which has proven successful at achieving high-speed compression in previous research. Several different predictive techniques (which includes polynomial extrapolation), along with CPU- and GPU-based parallelization approaches are discussed. The implementation successfully achieves throughput rates in excess of 6 GiB/s for compression and much higher rates for decompression using a 64-core AMD Opteron machine, achieving file-size reductions of, on average 9%. Furthermore the results of concurrent investigations into block-based parallel Huffman encoding and Zero-length Encoding are compared to the predictive scheme and it was found that the predictive scheme obtains approximately 4%-5% better compression ratios than the Zero-Length Encoder and is 25 times faster than Huffman encoding on an Intel Xeon E5 processor. The scheme may be well-suited to address the large network bandwidth requirements of the MeerKAT project. DA - 2013 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2013 T1 - Fast online predictive compression of radio astronomy data TI - Fast online predictive compression of radio astronomy data UR - http://hdl.handle.net/11427/21225 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/21225
dc.identifier.vancouvercitationHugo B. Fast online predictive compression of radio astronomy data. [ThesesThesis]. University of Cape Town ,Unknown ,Computer Science, 2013 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/21225en_ZA
dc.languageengen_ZA
dc.publisher.departmentComputer Scienceen_ZA
dc.publisher.facultyUnknownen_ZA
dc.publisher.institutionUniversity of Cape Townen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.titleFast online predictive compression of radio astronomy dataen_ZA
dc.typeMaster Thesis
dc.type.qualificationlevelMasters
dc.type.qualificationnameHonsen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesesThesisen_ZA
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