GPU computing in practice

Part of Scientific Computing in Practice lecture series at Aalto University.

Audience: Aalto employees and students looking for extensive intro into GPU computing.

About the course: The course covers the different models of GPU computing, such as basics of compiling and running GPU ready applications, using GPU libraries to do the math and finally writing your own code with CUDA.

Lecturer: Filippo Federici, D. Sc., COMP/Department of Applied Physics, Aalto University

Time, date: all four lectures in October 2017:

  • Ma 16.10.2017 klo 12:00-15:00
  • Ke 18.10.2017 klo 12:00-15:00
  • Ma 23.10.2017 klo 12:00-15:00
  • Ke 25.10.2017 klo 12:00-15:00

Place: Otaniemi, Otakaari 1, NOKIA (the auditorio next to the student’s hub/cafeteria in the main building, also know as U135a)

Cost: Free of charge for Aalto employees and students.

Registration: open for the registration

Credits (opintopisteet): Course certificate available on request to be shared at very end of the course. Since the main focus of the course is learning through experience, the students will be required to perform simulations for homework and hand in result report. Full course hours correspond roughly to 1 ECTS.

Other comments: Participants will be provided with access to Triton for running examples. Participants are expected to bring their own laptops. We will use SSH for Triton connection. One can follow the theoretical part without a laptop, though if you want to try the tutorial you’d better have one.

Additional course info at: filippo.federici -at- aalto.fi / ivan.degtyarenko -at- aalto.fi