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.
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
Does a similar job
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Cuckoo Filter Implementation in Go, Better Than Bloom Filters2016 · github.com · ▲181Cuckoo Filter implementation in Go, better than Bloom Filters (unmaintained) - irfansharif/cfilter
Cuckoo Filter: Practically better than Bloom filter implemented in Go2017 · github.com · ▲16Cuckoo Filter: Practically better than bloom filter - vedhavyas/cuckoo-filter
Cuckoo Filter in Ruby2017 · github.com · ▲74Pure Ruby Cuckoo Filter Implementation. Contribute to pawandubey/cuckoo_filter development by creating an account on GitHub.
I've built a locally running Perplexity clone2024 · github.com · ▲669The video demo runs a 7b Model on a normal gaming GPU. I think it already works quite well (accounting for the limited hardware power). :)
BloomSearch – Keyword search with hierarchical Bloom filters2025 · github.com · ▲66Hey HN! I got nerd-sniped by Bloom Filters this weekend, specifically for searching datasets with high "cardinality" (number of unique items). They're an _amazing_ data structure that, at a fixed size, tracks potential set membership. That means unlike normal b-tree indexes, they don't grow with the number of unique items in the dataset. This makes them great for "needle in a haystack" search (logs, document) as implementations like VictoriaMetrics and Bing's BitFunnel show. I've used them in the past, but they've never been center-stage in my projects. I wanted high cardinality keyword…
- BFBloom Filter2017 · sacert.github.io · ▲65
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