compression-methods

Huffman coding implementation for lossless file compression in Go

comprector is a compression method that will amaze you

Livid Lattices for Large Lineages of Chains and Ciphers

An educational compression experimentation toolkit built in Go. This CLI tool allows you to experiment with different compression algorithms, analyze their performance, and understand compression theory through hands-on examples. An educational compression experimentation toolkit.

This blog shares my research and insights on Large Language Models, Computer Vision, FPGA, and GPU architecture with kernel optimization. It serves as a hub for advanced concepts, practical implementations, and performance tuning in AI and high-performance computing. Disclaimer: Opinions expressed are my own and do not represent AMD.

High performance compression and encryption of string data using Vernam cipher in PHP.

A payload compression toolkit that makes it easy to create ideal data structures for LLMs; from training data to chain payloads.

My own hand-rolled compression util

Self Extracting GeoJSON build compressed GeoJSON distributed over JSONP in a compact, no dependencies Javascript file

Lossless compression algorithm. Input data are interpreted in different ways and the algorithm is searching for identical parts then. It's being bulit.

Information theory and methods of data compression - PUT Poznań 2018

PAIRL enforces efficient, cost-trackable communication between agents. It uses dual channels to avoid context errors and hallucinations.

my projects for the course of "data and image compression" at UPC (Universitat Politecnica de Catalunya)

Game Boy Compression Playground - detailed information related to Game Boy compression methods.

LZO 2.10 source + prebuilt binaries -- a real-time data compression library. Latest release (2.1.0) from www.lzop.org

Ravdec is a Python module implementing a lossless data compression algorithm designed by Ravin Kumar on September 19, 2016. This algorithm is designed exclusively for textual data, including alphabets, numbers, and symbols.

The Unified Latent-State Memory Fabric (UL-SMF) is a hardware-software co-designed memory compression fabric that solves the memory bottleneck in long-context Transformer inference. By combining FSQ with dynamic 16-dimensional latent mapping, UL-SMF compresses Key-Value (KV) cache tensors by up to 384x while maintaining >94% semantic retention.