Intel® Query Processing Library (Intel® QPL)
-
Updated
Jun 11, 2024 - C
Intel® Query Processing Library (Intel® QPL)
Up to 200x Faster Inner Products and Vector Similarity — for Python, JavaScript, Rust, C, and Swift, supporting f64, f32, f16 real & complex, i8, and binary vectors using SIMD for both x86 AVX2 & AVX-512 and Arm NEON & SVE 📐
SIMD Library for Evaluating Elementary Functions, vectorized libm and DFT
ADAM is an actively developed CSPRNG inspired by ISAAC64
⚡️⚡️⚡️Blazing fast correlation functions on the CPU.
SNU CSE Scalable High Performance Computing (M1522.006700) - 2023 Autumn
ChaCha20 C SIMD implementations - AVX512, AVX2, SSE2
Turbo Base64 - Fastest Base64 SIMD:SSE/AVX2/AVX512/Neon/Altivec - Faster than memcpy!
An implementation of Google's Encoded Polyline algorithm in AVX512 because why not. Perhaps the fastest and least portable polyline encoder out there?
X86-64 bilateral instruction tokenizer implemented in C. Supports the following processor extensions: AES, AVX, AVX2, AVX512, FMA, MMX, SSE, SSE2, SSE3, SSE4, x87(FPU), VMX. In order to ease testing, a diassembler which transforms tokens into compilable assembly (for NASM compiler) has been implemented.
Collection of optimized SIMD implementations for popular patterns
Add a description, image, and links to the avx512 topic page so that developers can more easily learn about it.
To associate your repository with the avx512 topic, visit your repo's landing page and select "manage topics."