S

SIMD

High-performance cryptographic suite featuring massive parallel execution of Secp256k1, SHA-256, and RIPEMD-160 using NVIDIA CUDA (GPU) and AVX2 (CPU). Includes a standalone CashAddr library.

Fast PRNG using WebAssembly and SIMD instructions.

The NAStJA framework provides an easy way to enable massively parallel simulations for a wide range of multi-physics applications based on stencil algorithms.

A high-performance CPU-based tool for searching compressed and uncompressed addresses, as well as puzzle-based private key and brainwallet searches. Commonly used in research projects such as Cyclone, Brainflayer, Keyhunt, BitCrack, Ecloop, Keyhunt CUDA, and BitCrack.For educational purposes

ZUC SM3 SM4 AVX2 optimized cryptographic algorithm implementation, about 6 times faster than some versions. And sm3 sm4 zuc cryptographic algorithm core implementation.

🚀 IronFox browser optimized for ARM/Snapdragon processors

• NEON SIMD instructions for 25-40% faster text processing • Direct GPU text rendering bypassing Android stack (40-60% faster) • Mobile-optimized DOM algorithms (20-35% faster) • VP9 video decoding optimizations (15-25% faster) • jQuery-like performance enhancements

Targets: Qualcomm Snapdragon, ARM Cortex-A78/A77/A76, OpenGL ES 3.0+

AES cryptographic library implemented in C/C++ with hardware acceleration using AES-NI and AVX2 instruction sets, and there is a generic version! They support AES-128, AES-192 and AES-256 bit key lengths, and multiple modes of operation: ECB, CBC, CTR, CFB128, OFB, GCM (basic building blocks).

This is a sha2 sha3 224 256 384 512 , Keccak-256 ,md5 ,sha1 ripemd160 Keccak224、256、384、512 hashing library written in C (compatible with C++), designed for extremely fast computations. It is deeply optimized to take advantage of the AVX2 instruction set in modern CPUs.

This is a generic c++ library with all kinds of functionality for use in my projects.

A Swift µ-Library of math extensions for SCNVector3, SCNQuaternion, SCNMatrix4

An attempt to implement SSE/AVX instructions in Python, mainly for fun.

A NAStJA Application

Provide a good solution to the CFM 2020 Challenge the hard way (hand writing the optimizer, directly use the Linear Algebra routines, use the most out of the multicore hardware).

Image filters, implemented in Assembly with SSE instructions for multiple data processing.

Academic Project.

The simd optimized escape code