MX-KMeans: Accelerating K-Means Clustering through Microscaling Quantization
K-Means clustering is a classical unsupervised learning method widely used for its simplicity, efficiency, and broad applicability. In this work, we first analyze the numerical distributions of representative K-Means datasets and identify an opportunity for low-precision acceleration through hardware-native microscalin...