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Google TPU의 핵심 혁신인 Systolic Array가 행렬 곱셈을 어떻게 극한까지 최적화하는지 완전 해부합니다. INT8 추론부터 bfloat16, XLA 컴파일러, TPU Pod까지 실제 숫자와 코드로 깊이 파헤칩니다.
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- Published on
딥러닝 연산의 80% 이상을 차지하는 행렬 곱셈이 GPU에서 어떻게 최적화되는가. 순진한 O(n³) 구현부터 캐시 블로킹, cuBLAS, 그리고 FlashAttention의 IO-aware 혁신까지 완전 해부한다.