Contenuti dettagliati del Corso
Introduction
- Meet the instructor.
- Create an account at courses.nvidia.com/join
Using JupyterLab
- Get familiar with your GPU-accelerated interactive JupyterLab environment.
Application Overview
- Orient yourself with a single GPU CUDA C++ application that will be the starting point for the course.
- Observe the current performance of the single GPU CUDA C++ application using Nsight Systems.
Introduction to CUDA Streams
- Learn the rules that govern concurrent CUDA stream behavior.
- Use multiple CUDA streams to perform concurrent host-to-device and device-to-host memory transfers.
- Utilize multiple CUDA streams for launching GPU kernels.
- Observe multiple streams in the Nsight Systems Visual Profiler timeline view.
Copy/Compute Overlap with CUDA Streams
- Learn the key concepts for effectively performing copy/compute overlap.
- Explore robust indexing strategies for the flexible use of copy/compute overlap in applications.
- Refactor the single-GPU CUDA C++ application to perform copy/compute overlap.
- See copy/compute overlap in the Nsight Systems visual profiler timeline.
Multiple GPUs with CUDA C++
- Learn the key concepts for effectively using multiple GPUs on a single node with CUDA C++.
- Explore robust indexing strategies for the flexible use of multiple GPUs in applications.
- Refactor the single-GPU CUDA C++ application to utilize multiple GPUs.
- See multiple-GPU utilization in the Nsight Systems Visual Profiler timeline.
Copy/Compute Overlap with Multiple GPUs
- Learn the key concepts for effectively performing copy/compute overlap on multiple GPUs.
- Explore robust indexing strategies for the flexible use of copy/compute overlap on multiple GPUs.
- Refactor the single-GPU CUDA C++ application to perform copy/compute overlap on multiple GPUs.
- Observe performance benefits for copy/compute overlap on multiple GPUs.
- See copy/compute overlap on multiple GPUs in the Nsight Systems visual profiler timeline.
Course Assessment
Final Review
- Review key learnings.
- Learn to build your own training environment from the DLI base environment container.
- Complete the workshop survey.