🎯 Bit-Vector Algorithms - abnv · Scour

mmgehlot/bitpolar: BitPolar: near-optimal vector quantization — 3-8 bit compression with zero training. 58 integrations across every major AI framework. 🎯Bit Vectors

github.com·2d·Hacker News·

Metal Quantized Attention: pulling M5 Max ahead with Int8 matrix multiplication 🗺️Region Inference

releases.drawthings.ai·19h·Hacker News·

TIL: Quantisation ∀Quantified Types

anup.io·5d·

Fujitsu One Compression (LLM Quantization) 📦Compression Algorithms

fujitsuresearch.github.io·17h·Hacker News·

Geekbench investigates up to 30% jump with Intel's iBOT — performance gain attributed to newly-vectorized instructions ⚡Instruction Fusion

tomshardware.com

·1d·

MinIO AIStor and Ampere® Computing Reference Architecture for High-Performance AI Inference 🏰Capability Machines

dzone.com·6d·

Beating Python’s GIL: Achieving a 130x Speedup in Batch Processing with Rust and Rayon 🦀MIR Optimization

medium.com·1d·

Accelerate CPU-based AI inference workloads using Intel AMX on Amazon EC2 🗺️Region Inference

aws.amazon.com·2d·

Iteratively optimizing an SPSC queue 🎯Ring Buffers

blog.c21-mac.com·3d·r/cpp·

Building a Production-Grade Vector Database in Rust: What We Shipped 🚂Cranelift Backend

ferres.io·1d·DEV·

On the properties of arithmetic crosscorrelation for sequences with coprime periods 🎯Bit Vectors

eprint.iacr.org·3d·

MXFP8 GEMM: Up to 99% of cuBLAS Performance Using CUDA and PTX 🔬Nanopasses

danielvegamyhre.github.io·4d·Hacker News·

The Synthesis Problem: Why I’m Building a New Logic Toolchain 🔬Nanopasses

llama.gs·6d·Hacker News·

Discord Engineers Add Distributed Tracing to Elixir's Actor Model Without Performance Penalty ✨Gleam

infoq.com·5d·

Pure C implementation of the TurboQuant paper (ICLR 2026) for KV cache compression in LLM inference. 🗺️Region Inference

github.com·1d·r/LocalLLaMA·

Speculative Decoding: Performance or Illusion? 🗺️Region Inference

specdecode-bench.github.io·5d·Hacker News·

Ray Tracer Performance Improvements and STL files 💬Smalltalk VMs

digitalflapjack.com·6d·

Finding-Fortune/Binary-Cellular-Automata: The Cellular Automata algorithm for cave generation computed with binary operations for a massive performance speed-up. >10x faster than other noise libraries at cave generation. ⚡Cache-Aware Algorithms

github.com·1d·r/proceduralgeneration·

From 30s to 200ms: Optimizing Multidimensional Time Series Analysis at Scale 📈Query Optimization

dzone.com·6d·

castnettech/mnemosyne: LLM context compression and retrieval engine. Zero dependencies. Sub-100ms queries. 40-70% token reduction. 🔄Subinterpreters

github.com·4d·r/SideProject·

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