Branch Prediction Insights
Jim discusses the evolution of branch prediction techniques, highlighting the shift from simple counters to complex systems resembling neural networks. He explains the substantial increase in complexity required to achieve higher accuracy, noting that while early methods achieved 85% accuracy with minimal bits, modern approaches demand vast amounts of data for near-perfect predictions. Additionally, he touches on the implications of mispredictions and the concept of invariance in understanding program execution.In this clip
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Lex Fridman Podcast
Jim Keller: Moore's Law, Microprocessors, and First Principles | Lex Fridman Podcast #70
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