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SESK: Stuff Everyone Should Know · sesk.info/ai-accelerators-matrix-math

Why do GPUs and TPUs fit neural network workloads especially well?

Neural networks perform huge amounts of matrix math.

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  1. They avoid arithmetic
  2. They accelerate matrix operations ✔
  3. They store unlimited data

Why: Layers batch many dot products into matrix multiplications. GPUs and TPUs provide specialized parallel hardware that can execute those regular operations efficiently.

Huh, didn't know that: Attention also packs queries, keys, and values into matrices for batched computation.

The dad joke
The GPU entered the matrix and felt right at home.
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References

Answer: They accelerate matrix operations. Layers batch many dot products into matrix multiplications. GPUs and TPUs provide specialized parallel hardware that can execute those regular operations efficiently.

  1. Google Research: Mixed-input matrix multiplication performance optimizations research.google/blog/mixed-input-matrix-multiplication-performance-optimizations
    Tensor Cores, which are specialized processing elements to accelerate matrix operations
    Checked 2026-10-10.

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