Course Description

Effective analysis and visualization of large-scale data can help users to comprehend the salient patterns and features in their data quickly. Modern high-resolution scientific simulations produce gigabytes to terabytes of data. Contemporary petaflop machines result in orders of magnitude higher data production rate as compared to data consumption rate. The data generation rate will soon reach exascale. To deal with extreme-scale data, the high performance computing and visualization community has been developing novel scalable data analysis and visualization algorithms. As part of this course, we will study research papers that demonstrate big data analysis and visualization techniques from the last decade or so. This course will also focus on state-of-the-art parallel and high performance data visualization techniques. The contents of this course will be based on research papers from top-tier journals and conferences such as IEEE TVCG, CGF, IEEE/ACM Supercomputing, IEEE Visualization, IEEE TPDS, IJHPCA, IEEE LDAV, EGPGV, EuroVis and EuroGraphics, IEEE Pacific Visualization, etc.