Title :
Vivaldi: A Domain-Specific Language for Volume Processing and Visualization on Distributed Heterogeneous Systems
Author :
Hyungsuk Choi ; Woohyuk Choi ; Tran Minh Quan ; Hildebrand, David G. C. ; Pfister, Hanspeter ; Won-Ki Jeong
Abstract :
As the size of image data from microscopes and telescopes increases, the need for high-throughput processing and visualization of large volumetric data has become more pressing. At the same time, many-core processors and GPU accelerators are commonplace, making high-performance distributed heterogeneous computing systems affordable. However, effectively utilizing GPU clusters is difficult for novice programmers, and even experienced programmers often fail to fully leverage the computing power of new parallel architectures due to their steep learning curve and programming complexity. In this paper, we propose Vivaldi, a new domain-specific language for volume processing and visualization on distributed heterogeneous computing systems. Vivaldi´s Python-like grammar and parallel processing abstractions provide flexible programming tools for non-experts to easily write high-performance parallel computing code. Vivaldi provides commonly used functions and numerical operators for customized visualization and high-throughput image processing applications. We demonstrate the performance and usability of Vivaldi on several examples ranging from volume rendering to image segmentation.
Keywords :
data visualisation; image processing; microscopes; parallel processing; rendering (computer graphics); telescopes; visual languages; GPU accelerators; GPU clusters; Vivaldi Python-like grammar; customized visualization; distributed heterogeneous systems; domain-specific language; flexible programming tools; high-performance distributed heterogeneous computing systems; high-performance parallel computing code; high-throughput image processing applications; high-throughput processing; image data; image segmentation; many-core processors; microscopes; numerical operators; parallel architectures; parallel processing abstractions; programming complexity; steep learning curve; telescopes; volume processing; volume rendering; volumetric data visualization; Computational modeling; Data models; Data visualization; Graphics processing units; Image classification; Parallel processing; Rendering (computer graphics); Domain-specific language; GPU computing; distributed heterogeneous systems; volume rendering;
Journal_Title :
Visualization and Computer Graphics, IEEE Transactions on
DOI :
10.1109/TVCG.2014.2346322