STEM与日常科技·英语30篇（3）
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GPU Tensor Cores and Matrix Multiplication
GPU张量核心与矩阵乘
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GPUs contain special units called tensor cores designed exclusively for multiplying huge matrices in one hardware step.
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While CPUs handle tasks sequentially, tensor cores crunch thousands of multiply-add operations simultaneously.
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This acceleration powers real-time video translation, where frames flow as pixel matrices needing constant transformation.
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Training a language model involves billions of matrix updates per second—tensor cores make that physically possible.
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Even smartphone GPUs now include tiny tensor units to run face filters or AR overlays without draining the battery.
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The math behind image recognition, speech synthesis, and weather simulation all rely on repeated, fast matrix math.
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Tensor cores don’t replace CPUs—they complement them by offloading math-heavy workloads with predictable patterns.
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Their efficiency explains why AI moved from labs to laptops, phones, and embedded devices within a single decade.