This course will focus on describing techniques for handling datasets larger than main memory in scientific visualization and computer graphics. Recently, several external memory techniques have been developed for a wide variety of graphics and visualization problems, including surface simplification, volume ren- dering, isosurface generation, ray tracing, surface reconstruction, and so on. This work has had significant impact given that in recent years there has been a rapid increase in the raw size of datasets. Several technological trends are contributing to this, such as the development of high-resolution 3D scanners, and the need to visualize ASCI-size (Accelerated Strategic Computing Initiative) datasets. An- other important push for this kind of technology is the growing speed gap between main memory and caches, such a gap penalizes algorithms which do not optimize for coherence of access. Because of these reasons, much research in computer graphics focuses on developing out-of-core (and often cache-friendly) techniques. This course reviews fundamental issues, current problems, and unresolved so- lutions, and presents an in-depth study of external memory algorithms developed in recent years. Its goal is to provide students and graphics researchers and pro- fessionals with an effective knowledge of current techniques, as well as the foun- dation to develop novel techniques on their own.
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