High Performance Computing Course – Starts 20 October

Todays’ supercomputers are the most powerful calculating machines ever invented, capable of performing more than a thousand million calculations every second. By using High Performance Computing (HPC) in your research, you can harness this power to conduct virtual experiments that are impossible in the real world or study Big Data problems.

Over 4 weeks we will look at:

• High Performance Computing: introducing supercomputing terminology and parallel computers.
• Parallel computing: using parallel processing to harness the power of all CPU cores for a single calculation on a Linux cluster, in the cloud and with GPU’s.
• Deep Learning: learn the latest techniques for designing, architecting, and deploying neural network-powered machine learning across a variety of application domains.
• Data analytics: learn Hadoop/Spark techniques to process data like Google/Amazon/Twitter and use R and python for Text Analysis.
• Data management: discuss privacy and open-data issues in science and tooling that is available in the research community.
• Scientific visualization: introducing various ways to process and present large-scale multidimensional data sets.

After the course you will have a broader and deeper knowledge and hands-on experience with HPC and data analytics to use in your own research.

The course is designed for PhD students and researchers who want to improve their data computing skills. Prior knowledge is not required, but basic programming skills will be helpful. The lectures are presented by reseachers of VU Amsterdam and UvA, in cooperation with SURFsara.

Practical information
Start course: October 20, 2017
Duration: 4 weeks
Cost: Free of charge for PhD students and researchers from VU Amsterdam and UvA. Non-UvA and VU: 300 Euro

On the website of the course you can find more information and register directly. For questions, please contact Peter Stol of  IT voor Onderzoek (ITvO).

The HPC course is organized by IT voor Onderzoek (ITvO) of VU Amsterdam in cooperation with UvA and SURFsara, and funded by the HPC board.