Keep it Simple, Stupid! Code with CUDA with GPGPU-Simulators & Docker & kickstart your Computing and Data Science career
What you’ll learn
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How to code with CUDA, but without a GPU!
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Basic knowladge about CUDA programming
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Ability to desing and implement CUDA parallel algorithms
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
-
2 hours on-demand video
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8 articles
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Full lifetime access
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Access on mobile and TV
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Certificate of completion
WELCOME!
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
- CUDA Coding Examples
WHY CUDA?
CUDA provides a general-purpose programming model which gives you access to the tremendous computational power of modern GPUs, as well as powerful libraries for machine learning, image processing, linear algebra, and parallel algorithms.
DISCLAIMER
Some of the images used in this course are copyrighted to NVIDIA.
- Any one who wants to learn CUDA programming, but does NOT have access to expensive GPUs
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