Learn CUDA with Docker | No NVIDIA GPUs required! Keep it Simple, Stupid! Code with CUDA with GPGPU-Simulators & Docker & kickstart your Computing and Data Science career Hot & New
What you’ll learn
- How to code with CUDA, but without a GPU!
- Basic knowladge about CUDA programming
- Ability to desing and implement CUDA parallel algorithms
- Basic C or C++ programming knowledge
We present you the long waited approach to Learn CUDA WITHOUT NVIDIA GPUS! Finally, you can learn CUDA just on your laptop, tablet or even on your mobile, and that’s it!
WHAT DO YOU LEARN?
We will demonstrate how you can learn CUDA with the simple use of: Docker: OS-level virtualization to deliver software in packages called containers and GPGPU-Sim, a cycle-level simulator modeling contemporary graphics processing units (GPUs) running GPU computing workloads written in CUDA or OpenCL. This course aims to introduce you with the NVIDIA’s CUDA parallel architecture and programming model in an easy-to-understand way. We plan to update the lessons and add more lessons and exercises every month!
- Virtualization basics
- Docker Essentials
- GPU Basics
- CUDA Installation
- CUDA Toolkit
- CUDA Threads and Blocks in various combinations
LIVE CLASS SERIES 2020!
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.
Students purchasing this course will receive free access to the interactive version (with Scientific code playgrounds) of this course from the SCIENTIFIC PROGRAMMING SCHOOL. Instructions to join are given in the bonus content section.