July 1, 2022, 1:11 a.m. | Felix Chern, Blake Hechtman, Andy Davis, Ruiqi Guo, David Majnemer, Sanjiv Kumar

cs.LG updates on arXiv.org arxiv.org

This paper presents a novel nearest neighbor search algorithm achieving TPU
(Google Tensor Processing Unit) peak performance, outperforming
state-of-the-art GPU algorithms with similar level of recall. The design of the
proposed algorithm is motivated by an accurate accelerator performance model
that takes into account both the memory and instruction bottlenecks. Our
algorithm comes with an analytical guarantee of recall in expectation and does
not require maintaining sophisticated index data structure or tuning, making it
suitable for applications with frequent updates. …

arxiv knn peak search tpu

Founding AI Engineer, Agents

@ Occam AI | New York

AI Engineer Intern, Agents

@ Occam AI | US

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Consultant - Artificial Intelligence & Data (Google Cloud Data Engineer) - MY / TH

@ Deloitte | Kuala Lumpur, MY