The Heterogeneous Computing group, part of SINTEF Mathematics and Cybernetics, perform world class research and consulting in high-performance, parallel scientific computing and visualization. Our goal is to combine the parallelism of traditional multi-core CPUs and accelerator cores to deliver unprecedented levels of performance.
We developed a novel approach for interactive visualization of isogeometric analysis results, ensuring correct, i.e., pixel-accurate geometry of the volume including its bounding surfaces.
Interactive rendering of large models require research both in geometrical representations and computer graphics. Our main research focus is on high-quality rendering of smooth surfaces.
Our research group was founded to study the potential for general purpose GPU computing. Ever since, we perform research on hardware adapted algorithms and how to use GPUs in multi-disiplanary teams.
We develop enabling technology for virtual and augmented reality, both for entertainment and proffesional use. Virtual and augmented reality has the potential to be a game changer in how we interact with computers. Our research is focused on realtime algorithms that help unleash this potential.
Deep Learning use advances in machine learning and GPU computing to solve complex problems. The two most known application areas are image classification and speech recognition. We perform research both on how to tackle new applications with deep learning and how to efficiently use the trained models in real time.