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AVX2

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18:31
2026-09-16
opensource.googleblog.com
ai-research

We've created the first vectorized Quicksort

Google researchers built the first portable vectorized Quicksort, using Highway's portable SIMD functions to run on six instruction sets across three architectures, and reported a 9-19x speedup over t…

04:00
2026-09-16
arxiv.org
large-language-models

Breaking the 1.58-bit Barrier for Ternary LLMs

A new arXiv paper (2609.16338v1) introduces BITCOS, a distribution-adaptive storage layout for ternary LLMs that costs 2 − z bits per weight given a zero density z, after measuring 29 ternary models a…

15:00
2026-09-07
github.com
artificial-intelligence

NanoGEMM – Bare-Metal AVX2 GEMM in ~100KB, Faster Than NumPy

NanoGEMM, a bare-metal AVX2/FMA matrix multiplication engine, claims to outperform NumPy 2.2.3 on small-to-medium matrices, achieving a 2.83x speedup on 16x16 float32 matrices (1.23 µs vs 3.21 µs) but…

13:54
2026-08-21
dev.to
large-language-models

I Ran a 284B-Parameter LLM From 3.2GB of RAM — in Plain C

A developer built a C99 inference engine that runs DeepSeek-V4-Flash, a 284B-parameter mixture-of-experts model, on a laptop with just 3.2GB of RAM by streaming weights off NVMe and caching only the e…

07:05
2026-07-13
github.com
large-language-models

Llambda.lisp an LLM Engine in Pure Common Lisp

Llambda.lisp, a pure Common Lisp inference engine for running quantized large language models from .gguf files, achieves C-level throughput using AVX2/FMA acceleration and multi-threading without wrap…

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