Practice question · Multiple choice
GPUs were designed to transform vertices for games and turned out to be what deep learning needed. What made the transfer possible?
Hints
- Write down the core operation of a rendering pipeline and of a neural network forward pass.
- Ask what the two have in common at the level of arithmetic.
Show the answer
D. Both are dominated by matrix multiplication over large arrays
Why
Both are chains of matrix multiplies over large arrays with no dependencies between elements, which is precisely what thousands of simple parallel cores are for. The convergence was accidental and consequential. NVIDIA later added tensor cores specifically for it, and the deep learning boom followed the hardware.
Practise Applications of Linear Algebra in Computing
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