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.
Day #1 – November 3rd, 2019
Day #2 – November 4th, 2019
Tel Aviv – Enroll now
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.
Lunch included at Carlton Hotel.
Enroll to receive price and course information.
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Eliezer Peri St 10 (Carlton Hotel), Tel Aviv, Israel