J4.3
Using Graphical Processing Units (GPUs) to Accelerate Processing for Big Satellite Data: Equipping the Climate Science Community with Data for Modeling

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Tuesday, 4 February 2014: 9:00 AM
Room C105 (The Georgia World Congress Center )
Amanda O'Connor, Exelis Visual Information Solutions, Boulder, CO; and B. Justice and T. Harris

Graphics Processing Units (GPUs) are high-performance multiple-core processors capable of very high computational speeds and large data throughput. Modern GPUs are inexpensive and widely available commercially. These are general-purpose parallel processors with support for a variety of programming interfaces, including industry standard languages such as C. GPU implementations of algorithms that are well suited for parallel processing can often achieve speedups of several orders of magnitude over optimized CPU codes. Significant improvements in speeds for imagery orthorectification, bowtie correction for NPP-VIIRS, atmospheric correction/compensation, and image transformations like Independent Components Analsyis (ICA) have been achieved using GPU-based implementations. These preprocessing steps can be very time intensive and can prohibit scientific discoveries with large data sets because the initial computation is so top heavy. Additional optimizations, when factored in with GPU processing capabilities, can provide 50x 100x reduction in the time required to process large imagery. Exelis Visual Information Solutions (VIS) has implemented a CUDA based GPU processing frame work for accelerating ENVI and IDL processes that can best take advantage of parallelization. By speeding up image processing, imagery can successfully be used by first responders, scientist making rapid discoveries with near real time data, and provides an operational component to data centers needing to quickly process and disseminate data.