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Paper detail

Parallel Algorithms Align with Neural Execution

Neural algorithmic reasoners are parallel processors. Teaching them sequential algorithms contradicts this nature, rendering a significant share of their computations redundant. Parallel algorithms however may exploit their full computational power, therefore requiring fewer layers to be executed. This drastically reduces training times, as we observe when comparing parallel implementations of searching, sorting and finding strongly connected components to their sequential counterparts on the CLRS framework. Additionally, parallel versions achieve (often strongly) superior predictive performance.

preprint2024arXivOpen access
Valerie EngelmayerDobrik GeorgievPetar Veličković
Machine Learning
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Valerie EngelmayerDobrik GeorgievPetar Veličković

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