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Real-Time Adaptive Lossless Hyperspectral Image Compression using CCSDS on Parallel GPGPU and Multicore Processor SystemsThe proposed CCSDS (Consultative Committee for Space Data Systems) Lossless Hyperspectral Image Compression Algorithm was designed to facilitate a fast hardware implementation. This paper analyses that algorithm with regard to available parallelism and describes fast parallel implementations in software for GPGPU and Multicore CPU architectures. We show that careful software implementation, using hardware acceleration in the form of GPGPUs or even just multicore processors, can exceed the performance of existing hardware and software implementations by up to 11x and break the real-time barrier for the first time for a typical test application.
Document ID
20130010586
Document Type
Conference Paper
External Source(s)
Authors
Hopson, Ben (Edinburgh Univ. United Kingdom)
Benkrid, Khaled (Edinburgh Univ. United Kingdom)
Keymeulen, Didier (Jet Propulsion Lab., California Inst. of Tech. Pasadena, CA, United States)
Aranki, Nazeeh (Jet Propulsion Lab., California Inst. of Tech. Pasadena, CA, United States)
Klimesh, Matt (Jet Propulsion Lab., California Inst. of Tech. Pasadena, CA, United States)
Kiely, Aaron (Jet Propulsion Lab., California Inst. of Tech. Pasadena, CA, United States)
Date Acquired
August 27, 2013
Publication Date
June 25, 2012
Subject Category
Computer Programming and Software
Meeting Information
2012 NASA/ESA Conference on Adaptive Hardware and Systems (AHS)(Nuremberg)
Distribution Limits
Public
Copyright
Other
Keywords
realtime
hyperspectral
multicore
GPGPU
parallel
Lossless
adaptive filter
image compression