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Introduction to GPU Architecture and Programming
The "Introduction to GPU Architecture and Programming" course explains the internal design of GPUs and their use in parallel workloads like AI, gaming, and simulations. You’ll explore instruction sets, memory hierarchies, and programming models like CUDA. As GPUs are often targeted in cyberattacks for cryptojacking or data theft, understanding their vulnerabilities is critical. This course discusses how GPU-level exploits can bypass traditional CPU-based defenses and the importance of securing multi-GPU systems in cloud and enterprise environments. Learn how to program GPUs efficiently while minimizing attack surfaces.
Course Overview
None
Learning Objectives
- Introduction to GPU Architecture and Programming
- Understand the architecture and parallel processing capabilities of Graphics Processing Units (GPUs).
- Learn the basics of GPU programming models like CUDA and OpenCL.
- Explore memory management and optimization techniques for GPU programming.
- Identify applications where GPU acceleration provides significant performance gains.
- Appreciate how GPUs accelerate computationally intensive tasks in cybersecurity, such as password cracking and intrusion detection.
Framework Connections
The materials within this course focus on the NICE Framework Task, Knowledge, and Skill statements identified within the indicated NICE Framework component(s):
Competency Areas
Feedback
If you would like to provide feedback on this course, please e-mail the NICCS team at NICCS@mail.cisa.dhs.gov. Please keep in mind that NICCS does not own this course or accept payment for course entry. If you have questions related to the details of this course, such as cost, prerequisites, how to register, etc., please contact the course training provider directly. You can find course training provider contact information by following the link that says “Visit course page for more information...” on this page.