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Dev tools · January 6, 2026

GPU Cuckoo Filter – faster queries than Blocked Bloom, with deletion

High-Performance GPU Cuckoo Filter. Contribute to tdortman/Cuckoo-GPU development by creating an account on GitHub.

GPU Cuckoo Filter – faster queries than Blocked Bloom, with deletion launched on January 6, 2026 with 32 votes, #628 of 14,584 launches that month and more than 95% of that year's launches.

Visit github.com ↗Alternativestop 4% of January 2026

In plain words

GPU Cuckoo Filter is a data structure tool designed for users who need fast membership queries with the ability to delete entries. It runs on GPUs and offers faster query performance compared to Blocked Bloom filters while supporting item removal, a feature Bloom filters lack. The tool is available as open-source code on GitHub and targets developers working with large datasets who require both speed and deletion capabilities.

written from the facts on this page · September 2026

From the sources

A high-performance, lock-free CUDA implementation of the Cuckoo Filter. This library is the companion code for the paper "Cuckoo-GPU: Accelerating Cuckoo Filters on Modern GPUs" . This library provides a GPU-accelerated Cuckoo Filter implementation optimized for high-throughput batch operations. Cuckoo Filters are space-efficient probabilistic data structures that support insertion, lookup, and deletion operations with a configurable false positive rate. Benchmarks at 95% load factor on an NVIDIA GH200 (H100 HBM3, 3.4 TB/s) with 16-bit fingerprints and equivalent space allocation for the Blocked Bloom Filter. The PCF runs on an Intel Xeon W9-3595X CPU (120from github.com

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