Flashlib brings Triton speed to classical ML

// 45d agoOPENSOURCE RELEASE

Flashlib brings Triton speed to classical ML

Flashlib is a GPU-accelerated library for classical machine learning operators like K-Means and PCA, built on Triton for maximum hardware efficiency. It features a unique predictive API that estimates runtime and memory usage in microseconds, enabling AI agents to budget workloads before execution.

// ANALYSIS

While deep learning has monopolized GPU optimization, classical ML has remained surprisingly inefficient; Flashlib finally applies modern kernel techniques to traditional data science.

–Outperforms NVIDIA cuML by up to 208x on TruncatedSVD and 26x on KMeans using H200 GPUs
–Built with Triton and CuteDSL, allowing for high-performance multi-precision execution (TF32, BF16, INT8)
–The "Flash-Informative" API provides CPU-based cost estimation, a critical requirement for autonomous agent resource planning
–Implementation of 15 primitives including DBSCAN and UMAP makes it a drop-in replacement for performance-starved scikit-learn pipelines

// TAGS

flashlibgpumltrainingdevtoolopen-sourceresearch

DISCOVERED

45d ago

2026-05-28

PUBLISHED

45d ago

2026-05-28

RELEVANCE

8/ 10

AUTHOR

Github Awesome

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