Advances, Applications and Performance of the Global Arrays Shared Memory Programming Toolkit
International Journal of High Performance Computing Applications
Visualization of high-resolution image collections on large tiled display walls
Future Generation Computer Systems
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The Parallel Computational Environment for Imaging Science, PiCEIS, is an image processing package designed for efficient execution on massively parallel computers. Through effective use of the aggregate resources of such computers, PiCEIS enables much larger and more accurate production processing using existing off the shelf hardware. Goals of PiCEIS are to decrease the difficulty of writing scalable parallel programs, reduce the time to add new functionalities, and provide for real-time interactive image processing. In part this is accomplished by the PiCEIS architecture, its ability to easily add additional modules, and the use of a shared-memory programming model based upon one-sided access to distributed shared memory. In this paper, we briefly describe the PiCEIS architecture and our shared memory programming tools and examine some typical techniques and algorithms. Initial image-processing performance testing is encouraging 驴 for very large image files, processing time is less than 10 seconds.