CUDA Spotlight: Anne Elster
GPU-Accelerated Imaging and Simulations
This week's Spotlight is on Anne C. Elster.
Anne is an Associate Professor at the Norwegian University of Science and Technology (NTNU), a CUDA Research Center and CUDA Teaching Center, where she runs the HPC-Lab (Heterogeneous and Parallel Computing Lab). She is also a Visiting Scientist at the University of Texas at Austin, a CUDA Teaching Center.
This interview is part of the CUDA Spotlight Series.
Q & A with Anne Elster
NVIDIA: Anne, what are some examples of projects you are working on at NTNU?
In addition, we have developed a nice real-time 3D snow simulation that we continue to add features to. This simulation can be used as a visual test-bed for numerical algorithms, terrain interactions, road planning and more.
At GTC 2013, we demonstrated how the snow simulation calculates 4+ million particles being affected by the wind field and terrain in real-time by harnessing the compute power of GPUs. We are also experimenting with adding SPH and other fluid techniques to simulate avalanches etc. [Read more about it here.]
NVIDIA: What are the advantages of GPU computing?
NVIDIA: What's on the horizon in the world of GPU computing?
NVIDIA: Can you share any programming techniques or tips with us?
NVIDIA: What courses do you teach?
I currently supervise four Ph.D. students at NTNU and co-supervise another four, including one (defacto) at the University of Texas at Austin where I spend each summer and my sabbaticals as a visiting scientist. In addition, I supervise nine masters students. More than 25 of my graduate students have completed theses on GPU and heterogeneous computing.
NVIDIA: Why do you like teaching?
NVIDIA: What is your advice for young people who are just learning about coding?
Bio for Anne Elster
Dr. Elster is an Associate Professor at the Norwegian University of Science and Technology (NTNU), where she runs the HPC-Lab (Heterogeneous and Parallel Computing Lab). She is also a Visiting Scientist at the University of Texas at Austin.
She served on the MPI standards committees (MPI and MPI-2) for Cornell and Schlumberger, respectively, and became a Senior Member of the IEEE in 2000. She has worked with GPGPU computing since 2006 and is the PI for NTNU's and UT Austin's CUDA Teaching Centers as well as the CUDA Research Center at NTNU.
Dr. Elster holds M.S. and Ph.D. degrees in Electrical Engineering from Cornell University where she explored various HPC systems in the late 1980s and early 1990s. After graduating from Cornell, she worked for Schlumberger in Austin before returning to academia via the University of Texas at Austin in 1997.