- Basic C/C++ competency, including familiarity with variable types, loops, conditional statements, functions, and array manipulations
- No previous knowledge of CUDA programming is assumed
At the conclusion of the workshop, participants will have an understanding of the fundamental tools and techniques for GPU- accelerating C/C++ applications with CUDA and be able to:
- Write code to be executed by a GPU accelerator
- Expose and express data and instruction-level parallelism in C/C++ applications using CUDA
- Utilize CUDA-managed memory and optimize memory migration using asynchronous prefetching
- Leverage command-line and visual profilers to guide your work
- Utilize concurrent streams for instruction-level parallelism
- Write GPU-accelerated CUDA C/C++ applications, or refactor existing CPU-only applications, using a profile-driven approach
This course is based on the materials for the corresponding NVIDIA DLI course. Since it is not an official DLI course, however, certification by NVIDIA is not possible at this point.
Module 1 -- Accelerating Applications with CUDA C/C++
- Writing, compiling, and running GPU code
- Controlling the parallel thread hierarchy
- Allocating and freeing memory for the GPU
Module 2 -- Managing Accelerated Application Memory with CUDA C/C++
- Profiling CUDA code with the command-line profiler
- Details on unified memory
- Optimizing unified memory management
Module 3 -- Asynchronous Streaming and Visual Profiling for Accelerated Applications with CUDA C/C++
- Profiling CUDA code with NVIDIA Nsight Systems
- Using concurrent CUDA streams
The program can be found here.
The course will be held in English.
Dr. Sebastian Kuckuk, certified NVIDIA DLI Ambassador.
The course is organised by NHR@FAU.
Prices and Eligibility
The course is open and free of charge for people from academia from the Member States (MS) of the European Union (EU) and Associated/Other Countries to the Horizon 2020 programme.
Please only register for the course if you are really going to attend. No-shows will be blacklisted and excluded from future events. If you want to withdraw your registration, please send an e-mail to email@example.com.
To be added to the wait list after the course has reached its maximum number of registrations send an e-mail to firstname.lastname@example.org with your name and university affiliation.