Fundamentals of Accelerated Computing with CUDA C/C++

Information

This tutorial teaches the fundamental tools and techniques for accelerating C/C++ applications to run on massively parallel GPUs with CUDA. You’ll learn how to write code, configure code parallelization with CUDA, optimize memory migration between the CPU and GPU accelerator, and implement the workflow that you’ve learned on a new task—accelerating a fully functional, but CPU-only, particle simulator for observable massive performance gains. At the end of the workshop, you’ll have access to additional resources to create new GPU- accelerated applications on your own.

At the end of the course a certificate will be given to whoever completes the activities.

Student´s prerequisites

• Basic C/C++ competency, including familiarity with variable types, loops, conditional statements,
  functions, and array manipulations
• No previous knowledge of CUDA programming is assumed

Materials

• Laptop computer with internet access capable of running the latest version of Chrome or Firefox.
• Each participant will be provided with dedicated access to a fully configured, GPU-accelerated server in the cloud.

Previous editions

• November 3, 2023. Open to Latin American higher education institutions, Online version
• April 22, 2024. Universidad Católica de Temuco, Temuco.
• April 23, 2024. Universidad de la Frontera, Temuco.

References

https://www.nlhpc.cl/nvidia-dli-workshops/
https://www.reuna.cl/2023/10/nvidia-dictara-talleres-virtuales-gratuitos-de-deep-learning-para-educacion-superior/
https://learn.nvidia.com/courses/course-detail?course_id=course-v1:DLI+C-AC-01+V1