Meet Flash-KMeans: An IO-Aware, Exact K-Means That Runs Over 200× Faster Than FAISS on GPUs
200×. That's how much faster Flash-KMeans runs k-means clustering on H200 GPUs versus FAISS—no approximations, just better IO-aware kernel design.
Why it matters
GPU compute optimization is becoming a critical competitive moat. Flash-KMeans demonstrates how algorithmic efficiency (IO awareness, eliminating atomic contention) can unlock massive speedups on existing hardware—directly impacting inference cost and latency for vector search and embedding operations at scale.
The key facts
9 to knowFlash-KMeans written in Triton GPU kernels
17.9× end-to-end speedup vs FAISS baseline
33× faster than cuML implementation
200×+ speedup over FAISS reported
Tested on NVIDIA H200
FlashAssign eliminates distance-matrix materialization
Sort-Inverse Update removes atomic contention bottleneck
Exact k-means—no mathematical approximation
Open-source release
Go to the source
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Publisher excerpt: Flash-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×…