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Openai/69256df6-133c-8005-ae25-fcf7c8af0f22
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==== - 大規模モデルはパラメータ数が膨大 → メモリ帯域と通信がボトルネック ==== * XLAはこれを解決するために、以下を最適化する： - 演算融合でメモリ転送を減らす - TPUメッシュでの通信パターンを自動生成 - GPUでも複雑な演算を効率的にカーネル化 💡 まとめ * TensorFlow：モデル定義と自動微分 * XLA：TensorFlowのグラフをコンパイルして高速化する * LLMの大規模学習では、XLAがあることでGPU/TPUの性能を最大限引き出せる もし希望であれば、私は「TensorFlow/XLAがTPUメッシュ通信をどう最適化しているか」を図解で示すイメージを作ることもできます。 作りますか？
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