- NVIDIA Course Overview and Objectives
- Introduction to NVIDIA CUDA SUIT
- Overview of NVIDIA GPU Development Ecosystem
- CUDA Toolkit Comprehensive GPU Programming Environment
- Setup and Installation of NVIDIA CUDA Suit ON GCP
- Setup and Installation of NVIDIA CUDA Suit ON Azure
- NVIDIA Nsight Compute: Integrated Development and Debugging Tools
- NVIDIA Nsight System: GPU-Accelerated Deep Learning Libraries
- NVIDIA Utilities
- NVIDIA System Management Interface (NVIDIA SMI)
- CUDA Utilities
- Nsight Compute Visual Studio Code Edition
What you'll learn
- GPU Architecture and CUDA Basics: Understand GPU architecture and write basic CUDA programs.
- Memory Management: Learn efficient memory allocation and data transfer techniques.
- Installation of NVIDIA CUDA Suit on Various Cloud like AWS, GCP and Azure.
- Performance Optimization: Apply advanced techniques to enhance CUDA application performance.
- Advanced CUDA Features and Libraries: Explore dynamic parallelism, unified memory, and CUDA libraries like cuBLAS and Thrust.
- Debugging and Profiling: Use tools to debug and profile CUDA applications, fixing common errors and optimizing code.
- Real-world Applications: Study applications and case studies in fields like machine learning and scientific computing.
- Hands-on Projects and Capstone: Implement a capstone project to apply and showcase your CUDA programming skills.
- CUDA Kernels and Parallel Programming: Master writing and optimizing CUDA kernels and handling parallel programming concepts.
Description
Unlock the full potential of NVIDIA GPUs with our comprehensive and free course on the NVIDIA CUDA Suite. This course is meticulously designed to cater to both beginners and experienced developers who are eager to delve into the world of parallel computing and GPU acceleration.
The NVIDIA CUDA Suite is a powerful platform for parallel computing that leverages the immense processing power of NVIDIA GPUs. Our course will guide you through the fundamentals of CUDA programming, starting with the basics and gradually advancing to more complex concepts. You will learn how to write efficient and optimized code that can significantly speed up computational tasks by harnessing the power of GPU parallelism.
Throughout the course, you will gain hands-on experience with real-world applications and examples. We will cover essential topics such as memory management, kernel functions, and performance optimization techniques. Additionally, you will explore advanced features like CUDA streams, events, and multi-GPU programming, which are crucial for developing high-performance applications.
Our course also includes detailed modules on integrating CUDA with popular programming languages like C++ and Python, making it easier for you to apply your newfound skills in various development environments. By the end of this course, you will have a solid understanding of the NVIDIA CUDA Suite and be well-equipped to tackle complex computational problems with ease.
Join us on this exciting journey to master GPU development with the NVIDIA CUDA Suite. Whether you are a student, researcher, or professional developer, this course will provide you with the knowledge and skills needed to excel in the rapidly evolving field of parallel computing. Enroll now and take the first step towards becoming an expert in GPU programming!
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instructer is just reading content from somewhere.
The course instructor reads the content from the web page. His delivery is very fast.
useless course literally