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12: GPUs - Can I, Should I, and How?
Manage episode 510879263 series 3660315
Jim McQuillan & Wolf and Jim McQuillan에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Jim McQuillan & Wolf and Jim McQuillan 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
It's Wolf's turn this episode, and this one required research!
GPUs obviously do tons of work. You see it every time you play a graphics intensive game. You know how crypto-miners are using them. You’ve heard AI companies using them for model building. You’ve got this hardware in your machine! Can you use it? Should you use it? Where even to start?
GPUs can help if your problems, data, systems, languages, and architecture align. GPU-based solutions won’t help everyone … but when they do help, oh boy do they really help.
Takeaways
Platform recommendations:
- NVIDIA: Richest ecosystem, start here if you have choice
- AMD: Improving rapidly, good for PyTorch workflows
- Apple Silicon: Excellent for unified memory workloads
Language recommendations:
- Python for quickest wins
- Rust/C++ for maximum control
- JavaScript for web applications
Links
Dave Farley explains what's wrong with Vibe coding https://youtu.be/1A6uPztchXk?si=mzEg4mpbTIjaihnP
How do graphics cards work https://youtu.be/h9Z4oGN89MU?si=JRrumRPfYU6a0A02
Hosts:
Jim McQuillan can be reached at [email protected]
Wolf can be reached at [email protected]
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Checkout our webpage at http://RuntimeArguments.fm
Theme music:
Dawn by nuer self, from the album Digital Sky
18 에피소드
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