CUDA Neural Networks

CUDA stands for Compute Unified Device Architecture, and it’s the reason popular deep learning libraries like Tensorflow & PyTorch are considered “GPU-accelerated”. CUDA is Nvidia’s programming platform that enables developers to leverage the full parallel processng capabilities of GPUs for deep learning applications. Almost all of the major deep learning libraries use CUDA under the hood, but it’s not really something that most developers think about often. In this episode, I’ll demo some progressively more complex CUDA examples by Nvidia to show you how using CUDA results in algorithmic speedups. We’ll use Nvidia’s profiler to clock speeds, then we’ll analyze a pure-CUDA neural network by Sergey Bugrov to understand how a full neural pipeline on the GPU looks like. Enjoy! TWITTER: https://bit.ly/2OHYLbB WEBSITE: https://bit.ly/2OoVPQF INSTAGRAM: https://bit.ly/312pLUb FACEBOOK: https://bit.ly/2OqOhx1 Subscribe for more educational videos! It means a lot to me. Notebook shown in the video can be found here. It’s kind of messy! It’s a compilation of various code samples by the Nvidia team + Sergey’s neural network. It’s also got the CUDA install steps for Colab: https://bit.ly/2uzg9FZ Nvidia’s CUDA Documentation: https://ift.tt/39p1USZ Some awesome tutorials by Nvidia on CUDA that helped me: https://ift.tt/2ShN7Uf https://ift.tt/3bqURLk https://ift.tt/2N22RIw Are you a total beginner to machine learning? Watch this: https://www.youtube.com/watch?v=Cr6VqTRO1v0 Learn Python: https://www.youtube.com/watch?v=T5pRlIbr6gg Live C Programming: https://www.youtube.com/watch?v=giF8XoPTMFg CUDA Explained: https://www.youtube.com/watch?v=1cHx1baKqq0 Hit the Join button above to sign up to become a member of my channel for access to exclusive live streams! Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w Credits: Nvidia team Sergei Bugrov Image assets are from across the Web, i take no credit for them And please support me on Patreon: https://ift.tt/2cMCk13