Government
Defense, Intelligence, Health & Human Services, Energy and other departments within government organizations are constantly looking for ways to improve system designs, mitigate risks, reduce costs, enhance services and leverage newer and better technologies.
AccelerEyes' software products are in use at many of the world's largest systems integrators performing important work for government agencies around the world. The U.S. National Institutes of Health and Center for Disease Control are using ArrayFire to leverage GPU technologies to find cures and better diagnose diseases.
AccelerEyes' software is revolutionizing productivity and performance for technical computing and leverages all assets across the government enterprise from desktop systems to large scale clusters housing GPUs.
Example Applications
ArrayFire can help educate students and support research in many application areas including:
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Powering Mars Research NASA and UAA in Anchorage |
Speedup: 5X |
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Powering Mars Research
Authors: NASA and UAA in Anchorage The main thrust of this research is improving mars rover image compression via GPUs and genetic algorithms. With AccelerEyes software, the researchers were able to achieve 5X speedups on the larger data sizes. The algorithm works by pairing neighboring pixels with a random one and then adjusting the random pixel based on whether it incrementally improves the original image. Babb described the algorithm as an embarrassingly parallel process, ideally suited to GPU acceleration. He estimates he has been able to achieve a 20 to 30 percent error reduction in subjects like fingerprints and satellite imagery. Last Updated: 6 Aug 2012 |
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Radar Image Formation System Planning Corporation |
Speedup: ~45X |
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Radar Image Formation
Authors: Gary Rubin and Earl Sager - System
Planning Corporation Radar imaging is computationally intensive. As a result, many imaging algorithms apply FFT-based approximations. While efficient, these algorithms sacrifice data fidelity for speed. Other algorithms better preserve information, but are often too slow for many applications. At System Planning Corporation (SPC) , we have implemented a SAR/ISAR imaging routine based on the Backprojection algorithm. Using AccelerEyes software, we have demonstrated speedups of roughly 45x for large datasets. Last Updated: 26 May 2010 |
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Radar Clutter Reduction System Planning Corporation |
Speedup: 5X - 10X |
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Radar Clutter Reduction
Authors: David Berger and Gary Rubin - System
Planning Corporation System Planning Corporation (SPC) uses AccelerEyes software to accelerate radar processing algorithms. The system processes raw data from marine navigation radars using a variety of thresholding techniques to extract real targets from clutter. This involves highly data-parallel processing in which each radar pulse is subjected to the same computations; very few operations occur across multiple pulses. Using AccelerEyes software, SPC has achieved 10x speed improvements relative to a Core i7-920 CPU and 5x improvements relative to a realtime DSP implementation. Last Updated: 26 May 2010 |
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Novel Algorithms for Linear Algebra SAIC |
Speedup: 3.5X |
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Novel Algorithms for LU Decomposition
Authors: Nolan Davis and Daniel Redig, SAIC Nolan Davis and Daniel Redig at SAIC recently presented work on Hybrid GPU/Multicore Solutions for Large Linear Algebra Problems where they developed a novel algorithm for LU decomposition, one of the most important routines in linear algebra. They presented a Hybrid CPU/GPU computing approach, where problems too large to fit in GPU memory can also be solved faster than using only the CPU. Last Updated: 26 Jul 2011 |
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Geolocation BAE Systems |
Speedup: 17X |
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Geolocation
Authors: BAE Systems Geolocation is the identification of the real-world geographic location of a target of interest. In this application, the system receives the signal with an array of several antennas and computes the direction of arrival of the radio energy by measuring the time difference of arrival (or the phase difference) at the different antennas. Last Updated: 13 Apr 2009 |
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Tsunami Modeling University of Minnesota, Boise State, Saint Scholastica , and NCAR |
Speedup: 3X - 5X |
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Tsunami Modeling
Authors: University of Minnesota, Boise State,
Saint Scholastica , and NCAR Natural catastrophic disasters like tsunamis commonly strike with little warning. For most people, tsunamis are underrated as major hazards. People sometimes wrongly believe that they occur infrequently and only along distant coasts. Tsunamis are usually caused by earthquakes. Seismic signals can give some margin of warning since the speed of tsunami waves travels at 1/30 the speed of seismic waves. Still there is little time between the creation of the tsunami and its impact making fast processing critical to producing effective warning systems. AccelerEyes software was used to run an RBF simulation on the GPU with a time to solution not available by other alternatives. Last Updated: 20 Dec 2009 |