High-Performance Visualization
Visual Computing Center, KAUST

We perform fundamental and applied research
in visualization and visual computing.

We specifically focus on the visualization of extreme-scale data, volume visualization, large-scale image and volume processing, multi-resolution techniques, data streaming and out-of-core processing, domain-specific languages for visualization, interactive segmentation, and GPU algorithms and architecture.

People

Alumni

Selected Publications

Browse selected publications here. See for a full list of publications below.

Teaching

We are currently teaching the following courses at KAUST.

CS 380: GPU and GPGPU Programming

CS 380: GPU and GPGPU Programming

This course is held each fall semester and covers the architecture and programming of GPUs (Graphics Processing Units). Covers both the traditional use of GPUs for graphics and visualization, as well as their use for general purpose computations (GPGPU). GPU many-core hardware architectures, shading and compute programming languages and APIs, programming vertex, geometry, and fragment shaders, programming with CUDA, Brook, OpenCL, stream computing, approaches to massively parallel computations, memory subsystems and caches, rasterization, texture mapping, linear algebra computations, alternative and future architectures.

AMCS / CS 247: Scientific Visualization

AMCS / CS 247: Scientific Visualization

This course is held each spring semester and covers the basics and applications of scientific visualization. Techniques for generating images and interactive visualizations of various types of experimentally measured, computer generated, or gathered data. Grid structures. Scalar field and volume visualization. Vector field and flow visualization. Tensor visualization. Applications in science, engineering, and medicine.