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不可忽视的是，Processing nearly one trillion genetic tokens demanded substantial infrastructure optimization. For the billion-parameter version, the team integrated FlashAttention-2 through NVIDIA's BioNeMo framework built upon NeMo, Megatron-LM, and Transformer Engine. To enable FlashAttention-2, they reconfigured feed-forward dimensions to ensure divisibility by attention head count—a strict compatibility requirement. Combined with bf16 mixed-precision training, these modifications achieved approximately 5x training acceleration and 4x micro-batch size enhancement on H100 80GB GPUs. For inference, implementing Megatron-Core DynamicInferenceContext with key-value caching produced over 400x faster generation compared to basic implementations.，这一点在whatsapp网页版@OFTLOL中也有详细论述
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