23 Mar 2019
This workshop teaches the fundamental tools and techniques for accelerating C/C++ applications to run on massively parallel GPUs with CUDA. Work your way through dozens of hands-on coding exercises using a live, GPU-enabled development environment in the cloud. Learn how to write code to be executed by a GPU accelerator, configure code parallelization using the CUDA thread hierarchy, manage and optimize memory migration between the CPU and GPU accelerator, leverage command line and visual profilers to guide your work, and utilize concurrent streams for instruction-level parallelism. Finish by implementing the workflow that you have 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 will have access to additional resources to create new GPU-accelerated applications on your own.
Learning Objectives:
At the conclusion of the workshop, you will have an understanding of the fundamental tools and techniques for GPU-accelerating C/C++ applications with CUDA, and will be able to:
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.
Write GPU-accelerated CUDA C/C++ applications, or refactor existing CPU-only applications, using a profile-driven approach.
Why Deep Learning Institute Hands-On Training?
Learn how to build deep learning and accelerated computing applications across a wide range of industry segments such as autonomous vehicles, digital content creation, finance, game development, and healthcare
Obtain guided hands-on experience using the most widely-used, industry-standard software, tools, and frameworks.
Gain real-world expertise through content designed in collaboration with industry leaders including the Children’s Hospital Los Angeles, Mayo Clinic, and PwC
Earn NVIDIA DLI Certification to demonstrate your subject matter competency and support professional career growth.
Details of the Workshop, Agenda and Prerequisites are attached in a separate flyer.
Workshop Setup Instructions:
1. Create an NVIDIA Developer account at http://courses.nvidia.com/join.
2. Make sure that Web Sockets works for you: * Test your laptop at http://websocketstest.com
* Under ENVIRONMENT, confirm that “Web Sockets” is checked yes.
* Under WEBSOCKETS (PORT 80), confirm that “Data Receive,” “Send,” and “Echo Test” are checked yes.
3. If there are issues with Web Sockets, try updating your browser. We recommend Chrome, Firefox, or Safari for an optimal performance. 4. Once onsite, visit http://courses.nvidia.com/dli-event and enter the event code provided by the instructor.
