Parallel Processing: Why GPUs Dominate AI

Preporato | AI for Engineers · Beginner ·🏭 MLOps & LLMOps ·1mo ago

About this lesson

- Why CPUs are huge, smart, and few (and why that makes them slow at scale) - Why GPUs have 16,000 tiny dumb cores and how they accidentally became AI chips - Why Google built the TPU and what a "systolic array" actually does? - Which chip wins for which workload, with three concrete jobs each Want to actually USE these chips? Hands-on labs: ▸ Deploy & Serve LLMs in Production (vLLM, Triton, TGI) https://preporato.com/labs/deploy-serve-llms-jupyter ▸ Fine-Tune an LLM with LoRA and QLoRA (Llama 3 8B) https://preporato.com/labs/fine-tune-llm-lora-jupyter ▸ All AI/ML labs https://preporato.com/labs CHAPTERS 0:00 Three chips, one job 0:20 The CPU 1:24 The GPU 3:10 The TPU 4:30 Who wins where 5:58 What's next #cpu #gpu #techexplained

Original Description

- Why CPUs are huge, smart, and few (and why that makes them slow at scale) - Why GPUs have 16,000 tiny dumb cores and how they accidentally became AI chips - Why Google built the TPU and what a "systolic array" actually does? - Which chip wins for which workload, with three concrete jobs each Want to actually USE these chips? Hands-on labs: ▸ Deploy & Serve LLMs in Production (vLLM, Triton, TGI) https://preporato.com/labs/deploy-serve-llms-jupyter ▸ Fine-Tune an LLM with LoRA and QLoRA (Llama 3 8B) https://preporato.com/labs/fine-tune-llm-lora-jupyter ▸ All AI/ML labs https://preporato.com/labs CHAPTERS 0:00 Three chips, one job 0:20 The CPU 1:24 The GPU 3:10 The TPU 4:30 Who wins where 5:58 What's next #cpu #gpu #techexplained
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Chapters (6)

Three chips, one job
0:20 The CPU
1:24 The GPU
3:10 The TPU
4:30 Who wins where
5:58 What's next
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