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Fundamentals of Accelerated Computing with CUDA C/C++

Course length

8 hours

Course Price


Fundamentals of Accelerated Computing with CUDA C/C++


Tomer Gal

> CTO at OpTeamizer Ltd
> An NVIDIA Preferred Partner, Deep Learning AI Institute
> A lecturer for the hi-tech industry and also in the academy
> DLI-certified Instructor of CUDA and Deep Learning courses
> NVIDIA DLI University Ambassador
> More than 10 years of GPU development experience
> Making many years of GPU development experience accessible to you and your team.

About the course


Upcoming dates

November 2, 2023, 9:00 AM-5:00 PM EST

Learning Objectives

At the conclusion of the workshop, you’ll 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


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

Technologies: NVIDIA® Nsight™, nsys

Certificate: Upon successful completion of the assessment, participants will receive an NVIDIA DLI certificate to recognize their subject matter competency and support professional career growth.

Hardware Requirements: Desktop or laptop computer 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.

Languages: English

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