Learn CUDA programming with GPGPU, kickstart your Big Data and Data Science Career!
WELCOME!
What you’ll learn
- GPU programming with CUDA.
- Understanding the basics of GPU architecture.
- Writing programs in CUDA language with the latest CUDA toolkit.
Course Content
- Let’s Learn CUDA Programming! –> 25 lectures • 1hr 26min.
- CUDA Lessons –> 6 lectures • 53min.
- Additonal contents – Interactive Playgrounds –> 2 lectures • 1min.
Requirements
- C/C++ programming.
- Visual Studio 2017 IDE (Free Community Edition).
- CUDA Toolkit (Version 10.0 Latest).
WELCOME!
This is the first CUDA programming course on the Udemy platform. It aims to introduce the NVIDIA’s CUDA parallel architecture and programming model in an easy-to-understand way where-ever appropriate. This is the first course of the Scientific Computing Essentials master class. We plan to update the lessons and add more lessons and exercises every month!
WHAT IS CUDA?
CUDA is a parallel computing platform and application programming interface (API) model created by NVIDIA. When it was first introduced, the name was an acronym for Compute Unified Device Architecture, but now it’s only called CUDA. Some of the images used in this course are copyrighted to nVIDIA.
WHAT DO YOU LEARN?
This course show and tell CUDA programming by developing simple examples with a growing degree of difficulty starting from the CUDA toolkit installation to coding with the help of block and threads and so on. This course covers:
- GPU Basics
- CUDA Installation
- CUDA Toolkit
- CUDA Threads and Blocks in various combinations
- CUDA Coding Examples
- Vector addition
- Matrix multiplication
This course comes with the first-ever online CUDA programming playgrounds. Students purchasing this course will receive free access to the interactive version of this course from the Scientific Programming School (SCIENTIFIC PROGRAMMING IO). Instruction are given in the bonus content section. Based on your earlier feedback, we are introducing a Zoom live class lecture series on this course through which we will explain different aspects of the Parallel and distributed computing and the High Performance Computing (HPC) systems software stack: Slurm, PBS Pro, OpenMP, MPI and CUDA! Live classes will be delivered through the Scientific Programming School, which is an interactive and advanced e-learning platform for learning scientific coding.
DISCLAIMER
Some of the images used in this course are copyrighted to NVIDIA.