Bringing UMAP Closer to the Speed of Light with GPU Acceleration

By Corey Nolet, V. Lafargue, Edward Raff, Thejaswi Nanditale, Tim Oates, John Zedlewski, Joshua Patterson. 2020

Subfields: Representation & Self-Supervised Learning, ML Systems & Hardware

Citations in the corpus

• NOMAD Projection (2025, unknown): “Alongside algorithmic advances, implementations such as t-SNE-cuda [3] and RapidsUMAP [17] have improved data mapping scalability by taking advantage of powerful GPU hardware.”