hashing

Jim Calabro introduces One Hash Bloom Filters, a variant that reduces hashing overhead in bloom filters, building on double-hashing techniques and Bluesky's production experience where bloom filters save millions of database queries per second.

一篇工程博客分享了如何通过将 Unreal 编辑器着色器哈希从缓慢的 SHA1 替换为引擎内已有的 xxHash，从而加速编辑器启动与资产处理。文章强调应避开已被高度优化的代码路径，转而寻找被忽视的低垂果实。

The ASRN Adaptive Sparse Recurrence Network introduces a copy layer for language models that looks up earlier occurrences of the current context via learned hash tables and reproduces what followed, achieving memory usage linear in sequence length as a cheaper alternative to full attention.

The article derives mathematical formulas for error distribution in consistent hashing systems, aiding in workload optimization across servers. It is a technical derivation that includes web assembly demos and references a Cloudflare blog post.

The article describes optimizations to the `gearhash` Rust crate, adding a NEON backend that doubles performance on ARM64 architectures, improving content-defined chunking for applications like Hugging Face's Xet client.

This paper proposes a method for cross-model memory transfer through target-side reader adaptation, using Engram hash memory and a lightweight reader, achieving 38.8 on QA tasks, and applicable to Agent memory updates and audits. The limitation is that it was only tested up to 9B models, with scaling laws unknown.

A technical blog post that explores sorting, hashing, and sketching algorithms on a dataset of 370,103 English words, measuring time and memory costs, with a focus on practical implementations like binary search, quicksort, and HyperLogLog.

Introduces BinaryPC, a training-free hashing-based sparse attention method for long-context LLMs that uses binary principal components to construct hash codes, preserving accuracy while improving decoding throughput by 3.56x over FlashAttention.

This article explains how implementing a Dense Arena Interner can drastically improve compiler performance by converting strings and structures into dense integers, enabling O(1) comparisons after an upfront hashing cost during lexing.

The Hugging Face CLI's `hf upload` command has been fully rewritten with single-pass hashing, multi-commits, and resumable uploads, available in version 1.20.0 for improved speed and cleanliness.

Bab is a family of hashing functions designed for peer-to-peer networks, enabling verifiable partial data. It was funded by the NLnet Foundation and the European Commission's Next Generation Internet programme.