This Fundamentals of Accelerated Computing with CUDA C/C++ and Python 2 Days course is now available in Israel, by an NVIDIA DLI-certified instructor Tomer Gal, CTO at OpTeamizer Ltd, an official NVIDIA Preferred Partner.

Course Name:
NVIDIA Fundamentals of Accelerated Computing with CUDA C/C++ and Python – 2 Days Course

Duration: 2 days

★ Course Description – Day 1:

This course explores how to use Numba—the just-in-time, type-specializing Python function compiler—to accelerate Python programs to run on massively parallel NVIDIA GPUs. You’ll learn how to:

Use Numba to compile CUDA kernels from NumPy universal functions (ufuncs)
Use Numba to create and launch custom CUDA kernels
Apply key GPU memory management techniques
Upon completion, you’ll be able to use Numba to compile and launch CUDA kernels to accelerate your Python applications on NVIDIA GPUs.

★ Course Description – Day 2:

Fundamentals of Accelerated Computing with CUDA C/C++ workshop hosted by NVIDIA DLI and OpTeamizer Ltd.

The CUDA computing platform enables the acceleration of CPU-only applications to run on the world’s fastest massively parallel GPUs. Experience C/C++ application acceleration by:

Accelerating CPU-only applications to run their latent parallelism on GPUs.

Utilizing essential CUDA memory management techniques to optimize accelerated applications.

Exposing accelerated application potential for concurrency and exploiting it with CUDA streams.

Leveraging command line and visual profiling to guide and check your work.

Upon completion, you’ll be able to accelerate and optimize existing C/C++ CPU-only applications using the most essential CUDA tools and techniques.

Intermission:
Lunch included at Carlton Hotel.

Price:
Enroll to receive price and course information.