Performance and scikit-learn (4/4)
Read OriginalThis technical article details performance experiments on the PairwiseDistancesReductions design in scikit-learn. It focuses on the PairwiseDistancesArgKmin implementation, examining hardware scalability (thread/core usage) and computational efficiency for Euclidean distance calculations. The analysis includes benchmarks, discussions of Amdahl's law, and uses Linux `perf` tools to profile CPU cycles and cache behavior in the k-nearest neighbors algorithm.
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