1 citations · 1 across the 4 of their papers we have counts for
4 papers
GPU-Accelerated ANNS: Quantized for Speed, Built for Change
Hunter McCoy, Zikun Wang, Prashant Pandey
Approximate nearest neighbor search (ANNS) is a core problem in machine learning and information retrieval applications. GPUs offer a promising path to high-performance ANNS: they…
WarpSpeed: A High-Performance Library for Concurrent GPU Hash Tables
Hunter McCoy, Prashant Pandey
GPU hash tables are increasingly used to accelerate data processing, but their limited functionality restricts adoption in large-scale data processing applications. Current limitat…
Adaptive Quotient Filters
Richard Wen, Hunter McCoy, David Tench +6
Adaptive filters, such as telescoping and adaptive cuckoo filters, update their representation upon detecting a false positive to avoid repeating the same error in the future. Adap…
High-Performance Filters For GPUs
Hunter McCoy, Steven Hofmeyr, Katherine Yelick +1
Filters approximately store a set of items while trading off accuracy for space-efficiency and can address the limited memory on accelerators, such as GPUs. However, there is a lac…