The Hiperwall Visualization Platform for Big Data Research

نویسندگان

  • M. Saleem
  • Hugo Valle
  • Stephen Brown
  • Veronica Winters
  • Akhtar Mahmood
چکیده

In the era of Big Data, with the increasing use of large-scale datadriven applications, the visualization of very large high-resolution images and extracting useful information (searching for specific targets or rare signal events) from these images can pose challenges to the current video-wall display technologies. At Bellarmine University, we have set up an Advanced Visualization and Computational Lab (AVCL) using a state-of-the-art next generation video-wall technology, called Hiperwall (Highly Interactive Parallelized Display Wall). The 16 feet wide by 4.5 feet high Hiperwall visualization system consists of eight display tiles that are arranged in a 4×2 tile format and has an effective resolution of 16.5 Megapixels. Using Hiperwall, we can perform interactive visual data analytics of large images by conducting comparative views of multiple large images in Astronomy and multiple data events in experimental High Energy Physics (HEP). Users can display a single large image across all the display tiles, or view many different images simultaneously on multiple display tiles. Hiperwall enables simultaneous visualization of multiple high resolution images and its contents on the entire display wall without loss of clarity. Hiperwall’s middleware also allows researchers in geographically diverse locations to collaborate on large scientific experiments. In this paper we will provide ∗[email protected][email protected][email protected] §[email protected][email protected] 1 ar X iv :1 80 2. 09 52 2v 1 [ cs .H C ] 2 6 Fe b 20 18 a description of a new generation of display wall setup at Bellarmine University that is based on the Hiperwall technology, which is a robust visualization system for Big Data research.

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عنوان ژورنال:
  • CoRR

دوره abs/1802.09522  شماره 

صفحات  -

تاریخ انتشار 2018