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From CUDA to Chips: Why Deep Learning Reshaped Computer Architecture
@nikolatesla
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2026-05-13 03:30:33
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- AlexNet (2012) on two GTX 580s demonstrated GPUs were 10–100x faster than CPUs for neural network matrix ops - Transformers are memory-bandwidth-bound (not compute-bound like CNNs) — driving the H100's NVLink + FP8 Transformer Engine design - AMD MI300X closed the training gap; inference optimization (Blackwell, Gaudi 3, Trainium) is the new battleground - The chip architecture that wins inference at scale defines the next 5-year AI infrastructure cycle
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