Nvidia CUDA in 100 Seconds
1,081,825
Published 2024-03-07
Sponsor Disclaimer: I was not paid to make this video, but Nvidia did hook me up with an RTX4090
#programming #gpu #100secondsofcode
💬 Chat with Me on Discord
discord.gg/fireship
🔗 Resources
CUDA nvda.ws/3SF2OCU
GTC nvda.ws/3uDuKzj
CPU vs GPU    • CPU vs GPU vs TPU vs DPU vs QPU Â
🔖 Topics Covered
- How does CUDA work?
- CUDA basics tutorial in C++
- Who invented CUDA?
- Difference between CPU and GPU
- CUDA quickstart
- How deep neural networks compute in parallel
- AI programming concepts
- How does a GPU wo
All Comments (21)
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Shoutout to Nvidia for hooking me up with an RTX4090 to run the code in this video, get the CUDA toolkit here nvda.ws/3SF2OCU
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Little know fact, CUDA is actually so fast, that it can bend spacetime and make 100 seconds last 3 minutes and 12 seconds, truly revolutionary.
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I've done a bit of CUDA in uni for a class in parallelism. Let me tell you, writting truly parallel code is a pain in the ass. Ain't no way all those scientists are writing CUDA code, probably some Python abstraction that uses C++ and CUDA underneath.
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The #1 computing platform for vendor lock-in
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0:36 this just taught me matrix multiplication, thanks
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Seeing "Hi Mom!" continue to be in your videos is such a beautiful thing. Hope you're holding up well
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0:45 IEEE 754 moment
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I did some CUDA programming assignments for my college Parallel Computing class. That course was the second hardest CS course I've ever taken (The hardest one is Compilers but that's in its own league). Human brains really weren't designed to think in parallel.
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1:09 still day zero of not mentioning AI
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ngl, I'm really loving how often these videos are being uploaded. It's often, but not so often that I feel overwhelmed and just spaced out enough that I feel a little excited when a new one comes out!
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Thanks! I was having this discussing with my coworkers the other day about what separates a gpu from a cpu and this was an excellent explanation!
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Bruh, are you my FBI agent? I just looked CUDA up a few hours ago.
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Wrote Cuda at university .. getting the indices, blocks etc right ... that was fun (also since thread count depends on the actual GPU model). For the final project, we were allowed to use libraries such as thrust which made my life a ton easier by abstracting away most of the fun stuff.
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Whoa, my universes are operating in parallel. I just learned about CUDA this morning for the first time, and here's a new fireship video about it.
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Not using or planning to use CUDA but man did this just help me make sense of some terms I see being thrown around! Awesome!
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Man, you are a genius. I wrote my masters thesis on CUDA and there's no way how I would be able to explain this in 100 seconds. Respect! 🎉
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Nice to see a video touching C++'s ecosystem for a change. Now make one about SYCL, so even people who don't find free RTX 4090 cards in their mailbox can get into high performance parallel computing using modern ISO C++ instead of custom CUDA syntax.
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1:39 Complier :D
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Yo I just wanted to say thank you for making this kind of stuff so interesting and digestible. You make these extremely complex, time intensive languages, apis, tools, etc., and make them incredibly approachable. Love your content. Cheers.
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Great presentation of the topic of CUDA architecture and Nvidia GPUs in such a compact and fast form. As always, brilliant video!
