VU University Amsterdam selected as a CUDA Teaching Center

CUDA Teaching Centers

We are proud to announce that the VU University Amsterdam has been selected as a CUDA Teaching Center by NVIDIA, the world leader in visual and high-performance computing. The award follows the submission of a proposal by Dr. Rob van Nieuwpoort, assistant professor at the Faculty of Sciences, department of computer sciences.

The VU University is the first and only university in the Netherlands to receive this honor. The award is recognition for our ongoing commitment to advance the state of art in parallel computing education using CUDA.

CUDA is NVIDIA's parallel computing architecture that enables dramatic increases in computing performance by harnessing the power of graphics processing units (GPUs). CUDA Teaching Centers are recognized institutions that have integrated GPU computing techniques into their mainstream computer science curriculum.

Dr. van Nieuwpoort teaches GPU computing in the computer science master program, and has organized GPU-related training events, such as in-depth courses for PhD students and summer-schools for bachelor students. With this selection, the University becomes part of a large and strong community of over 480 leading institutions around the world dedicated to GPU computing education and research.

As part of the CUDA Teaching Center program, NVIDIA has donated GPUs to support the University’s teaching efforts. The equipment will be integrated into our existing DAS-4 infrastructure, a six-cluster wide-area distributed system designed by the Advanced School for Computing and Imaging (ASCI). DAS-4 is specifically designed for heterogeneous computing platform and for experiments with accelerators such as GPUs. The goal of DAS-4 is to provide a common nation-wide computational infrastructure for researchers within ASCI, who work on various aspects of parallel, distributed, grid and cloud computing.

Dr. van Nieuwpoort's current research activities include the use of GPUs for radio astronomy, increasing the capabilities of the largest radio telescope in the world, LOFAR, and future instruments such as the SKA. This research is done in collaboration with ASTRON, the Netherlands institute for radio astronomy.

Here is the course material:
class 1: Introduction, performance metrics & analysis.
class 2: Many-core hardware.
class 3: Cuda basics.
class 4: Advanced Cuda.
class 5: Many-core processing for the LOFAR telescope.

Also, we teach hands-on experience with CUDA and/or OpenCL in the parallel programming practical.

For contact information and more information on CUDA educational programs at the VU, see

For more information the NVIDIA CUDA Teaching Center Program, see

For more information on DAS-4, see

Rob van Nieuwpoort /