EGPGV19: Eurographics Symposium on Parallel Graphics and Visualization

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https://diglib.eg.org/handle/10.2312/2632789

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Browsing EGPGV19: Eurographics Symposium on Parallel Graphics and Visualization by Subject "Computer graphics"

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    Efficient Point Merging Using Data Parallel Techniques
    (The Eurographics Association, 2019) Yenpure, Abhishek; Childs, Hank; Moreland, Kenneth; Childs, Hank and Frey, Steffen
    We study the problem of merging three-dimensional points that are nearby or coincident. We introduce a fast, efficient approach that uses data parallel techniques for execution in various shared-memory environments. Our technique incorporates a heuristic for efficiently clustering spatially close points together, which is one reason our method performs well against other methods. We then compare our approach against methods of a widely-used scientific visualization library accompanied by a performance study that shows our approach works well with different kinds of parallel hardware (many-core CPUs and NVIDIA GPUs) and data sets of various sizes.
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    Statistical Analysis of Parallel Data Uploading using OpenGL
    (The Eurographics Association, 2019) Wiedemann, Markus; Kranzlmüller, Dieter; Childs, Hank and Frey, Steffen
    Modern real-time visualizations of large-scale datasets require constant high frame rates while their datasets might exceed the available graphics memory. This requires sophisticated upload strategies from host memory to the memory of the graphics cards. A possible solution uses outsourcing of all data uploads onto concurrent threads and disconnecting prohibitive data dependencies. OpenGL provides a variety of functions and parameters but not all allow minimal interference on rendering. In this work, we present a thorough and statistically sound analysis of various effects introduced by choosing different input parameters, such as size, partitioning and number of threads for uploading, as well as combinations of buffer usage hints and uploading functions. This approach provides insight into the problem and offers a basis for future optimizations.