Meet Flash-KMeans: An IO-Aware, Exact K-Means That Runs Over 200× Faster Than FAISS on GPUs
Quick Answer
Flash-KMeans is an open-source, IO-aware k-means implementation that operates over 200× faster than FAISS on NVIDIA H200 GPUs.
Quick Take
Flash-KMeans is an open-source, IO-aware k-means implementation that operates over 200× faster than FAISS on NVIDIA H200 GPUs. It achieves 17.9× end-to-end and 33× speedup over cuML by optimizing distance calculations and updating mechanisms without approximating results. This advancement significantly enhances performance for data scientists and machine learning practitioners.
Key Points
- Flash-KMeans uses Triton GPU kernels for efficient k-means clustering.
- Eliminates distance-matrix materialization with FlashAssign for faster processing.
- Sort-Inverse Update reduces atomic contention, enhancing performance.
- Achieves 17.9× speedup end-to-end and 33× over cuML.
- Over 200× faster than FAISS, revolutionizing k-means implementations.
Article Excerpt
From source RSS / original summaryFlash-KMeans is an open-source, IO-aware implementation of standard Lloyd's k-means in Triton GPU kernels. It does not change the math or approximate. FlashAssign removes distance-matrix materialization; Sort-Inverse Update eliminates atomic contention. On an NVIDIA H200, it reports 17. 9× end-to-end, 33× over cuML, and over 200× over FAISS. The post Meet Flash-KMeans: An IO-Aware, Exact K-Means That Runs Over 200× Faster Than FAISS on GPUs appeared first on MarkTechPost.
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