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Astronomers from the California Institute of Technology (Caltech) and the University of Arizona have released the largest data set ever collected that documents the brightening and dimming of stars and other celestial objects—two hundred million in total.
The night sky is filled with objects like asteroids that dash across the sky and others—like exploding stars and variable stars-that flash, dim, and brighten. Studying such phenomena can help astronomers better understand the evolution of stars, massive black holes in the centers of galaxies, and the structure of the Milky Way. These types of objects were also essential for the recent discovery of dark energy-the mysterious energy that dominates the expansion of the universe—which earned last year’s Nobel Prize.
Using the Catalina Real-Time Transient Survey (CRTS), a project led by Caltech and including CACR staff Andrew Drake and Matthew Graham, the astronomers systematically scanned the heavens for these dynamic objects, producing an unprecedented data set that will allow scientists worldwide to pursue new research.
Read the full Caltech press release here.
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“AIDA: a language for programming in algorithmic pictures”
Professor Nikolay N. Mirenkov
School of Computer Science and Engineering
University of Aizu
February 14, 2012
11:00AM
Powell-Booth Room 100
AIDA is a language of algorithmic CyberFrames and CyberFilms within the Filmification modeling (F-modeling) environment where pictures and moving pictures are used as super-characters for the representation of features of computational algorithms and data structures. AIDA stands for “animation and images to develop algorithms.”Within this approach algorithms are considered as activities in 4-D space-time where some “data spaces” are traversed by “fronts of computation” and necessary operations are performed during these traversal processes. There are compound pictures to define algorithmic steps (called Algorithmic CyberFrames) and generic pictures to define the contents of compound pictures. Compound pictures are assembled into special series to represent Algorithmic CyberScenes and Algorithmic CyberFilms. The generic and compound pictures are developed and acquired in special libraries (galleries) of an open type where supportive pictures of embedded clarity annotations are also included. In this approach, the end user usually does not create new pictures,but do get them from existing galleries. In this presentation, features of AIDAand F-modeling environmentwill be explained and examples of programs(including fluid dynamic simulation) will be demonstrated.
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Thursday January 19, 2012
3PM | Powell Booth Room 100 P-B
“IMPATIENT MRI: Illinois Massively Parallel Acceleration Toolkit for Image reconstruction with ENhanced Throughput in MRI”
Jiading Gai
University of Illinois at Urbana-Champaign
Computational acceleration on graphics processing units (GPUs) can make advanced magnetic resonance imaging (MRI) reconstruction algorithms attractive in clinical settings, thereby improving the quality of MR images across a broad spectrum of applications. This talk describes the Illinois Massively Parallel Acceleration Toolkit for Image reconstruction with ENhanced Throughput in MRI (IMPATIENT MRI), a reconstruction utility that enables advanced techniques within clinically relevant computation times by using the computational power available in low-cost graphics processing cards. We demonstrate that the Toeplitz code running on a NVIDIA Tesla C1060 (field-corrected, SENSE) can reduce a one-week long, non-Cartesian 3D 1mm3 high-resolution, whole brain DTI reconstruction (4-channel acquisition) to 4.3 hours.
