Vector Hashing

What is Vector Hashing?

Vector hashing is one method of optimization searching for vector values, or for the "nearest" vector in a search space. This has applications in AI of optimizing vector databases, semantic lookup (of embedding vectors), RAG architectural lookups, and nearest-neighbor algorithms. See also: vector databases, vector optimizations, vector sparsity, vector pruning.

Research on Vector Hashing

Research papers include:

• Hackerllama, January 7, 2024, Sentence Embeddings. Introduction to Sentence Embeddings, https://osanseviero.github.io/hackerllama/blog/posts/sentence_embeddings/
• M Sponner, B Waschneck, A Kumar , 2024, Adapting Neural Networks at Runtime: Current Trends in At-Runtime Optimizations for Deep Learning, ACM Computing Surveys,, PDF: https://dl.acm.org/doi/pdf/10.1145/3657283 (Survey of various adaptive inference optimization techniques with much focus on image and video processing optimization for LLMs.)
• David Spuler, March 2024, Chapter 18. Parallel Data Structures, Generative AI in C++: Coding Transformers and LLMs, https://www.amazon.com/dp/B0CXJKCWX9
• Yikun Han, Chunjiang Liu, Pengfei Wang, 18 Oct 2023, A Comprehensive Survey on Vector Database: Storage and Retrieval Technique, Challenge, https://arxiv.org/abs/2310.11703
• Ala-Eddine Benrazek, Zineddine Kouahla, Brahim Farou, Hamid Seridi, Ibtissem Kemouguette, 28 Aug 2024, Efficient k-NN Search in IoT Data: Overlap Optimization in Tree-Based Indexing Structures, https://arxiv.org/abs/2408.16036
• David Spuler, March 2024, Vector Hashing, in Generative AI in C++, https://www.aussieai.com/book/ch18-vector-hasing
• Duy-Thanh Nguyen, Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda, 9 Feb 2023, DeepCAM: A Fully CAM-based Inference Accelerator with Variable Hash Lengths for Energy-efficient Deep Neural Networks, https://arxiv.org/abs/2302.04712
• Aditya Desai, Shuo Yang, Alejandro Cuadron, Ana Klimovic, Matei Zaharia, Joseph E. Gonzalez, Ion Stoica, 19 Dec 2024, HashAttention: Semantic Sparsity for Faster Inference, https://arxiv.org/abs/2412.14468
• Uri Merhav, Dec 30, 2024, Vector Similarity Search is Hopeless. A pre-baked notion of similarity is inherently flawed and doomed to fail. We can do better. https://urimerhav.medium.com/vector-similarity-search-is-hopeless-7251a855b4bd

AI Books from Aussie AI

The Sweetest Lesson: Your Brain Versus AI: new book on AI intelligence theory: Your brain is 50 times bigger than the best AI engines. Truly intelligent AI will require more compute! Another case of the bitter lesson? Maybe it's the opposite of that: the sweetest lesson. Get your copy from Amazon: The Sweetest Lesson

RAG Optimization: Accurate and Efficient LLM Applications: new book on RAG architectures: Smarter RAG Faster RAG Cheaper RAG Agentic RAG RAG reasoning Get your copy from Amazon: RAG Optimization

Generative AI Applications book: Deciding on your AI project Planning for success and safety Designs and LLM architectures Expediting development Implementation and deployment Get your copy from Amazon: Generative AI Applications

Generative AI programming book: Generative AI coding in C++ Transformer engine speedups LLM models Phone and desktop AI Code examples Research citations Get your copy from Amazon: Generative AI in C++

CUDA C++ Optimization book: Faster CUDA C++ kernels Optimization tools & techniques Compute optimization Memory optimization Get your copy from Amazon: CUDA C++ Optimization

CUDA C++ Debugging book: Debugging CUDA C++ kernels Tools & techniques Self-testing & reliability Common GPU kernel bugs Get your copy from Amazon: CUDA C++ Debugging

More AI Research Topics

Read more about:

• 500+ LLM Inference Optimization Techniques
• What's Hot in LLM Inference Optimization in 2025?
• Inference Optimization Research
• « Research Home