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Reiner Pope – The math behind how LLMs are trained and served

Dwarkesh Podcast · 29 APR 2026 · 134 min

Reiner Pope delivers a blackboard lecture on the mathematical and hardware principles behind training and serving large language models. He explains how batch size, sparsity, and various parallelism strategies (expert, pipeline) impact late…

LLM trainingLLM inferenceBatch sizeLatency optimizationCost analysisRoofline analysisMemory bandwidthCompute performanceKV CacheSparsityMixture of ExpertsExpert parallelismData center architectureScale up networkScale out networkPipeline parallelismMicrobatchingMemory capacityChinchilla scalingRL generationAPI pricingContext lengthCryptographic ciphersNeural network architectureReversible networks