Training an LLM in Swift, Part 1: Taking matrix mult from Gflop/s to Tflop/s | Hacker News
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2 min readKey summary
A Hacker News thread highlights an article on optimizing Swift matrix multiplication for LLM training on Apple hardware.
The piece focuses on low-level tuning that could push performance from gigaflops toward teraflops.
Discussion also raises Apple AMX instructions and whether newer chips like M4 expose similar acceleration.
The topic matters because Swift currently lacks much practical guidance on squeezing maximum performance from ML workloads.
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