JIHAD EL SANA

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.