GitHub

Parallel network simplex algorithm for the minimum cost flow problem.

This code is structured as a standalone tool to use as a solver for DIMACS minimum cost flow problem files. Solution is then given as a DIMACS minimum cost flow solution file optionally with flow ...
TechCrunch

Google unveils TurboQuant, a new AI memory compression algorithm — and yes, the internet ...

If Google’s AI researchers had a sense of humor, they would have called TurboQuant, the new, ultra-efficient AI memory compression algorithm announced Tuesday, “Pied Piper” — or, at least that’s what ...
Seeking Alpha

Google reveals algorithms to address AI memory challenges; memory and storage stocks drop

Google (GOOG)(GOOGL) revealed a set of new algorithms today designed to reduce the amount of memory needed to run large language models and vector search engines. The algorithms introduced by Google ...
VentureBeat

Google's new TurboQuant algorithm speeds up AI memory 8x, cutting costs by 50% or more

As Large Language Models (LLMs) expand their context windows to process massive documents and intricate conversations, they encounter a brutal hardware reality known as the "Key-Value (KV) cache ...
IEEE

The optimization of mixture ratio of model sand based on Simplex Particle Swarm ...

Abstract: Model sand composed of several kinds of sand according to a certain proportion to meet required sand gradation is often needed in model test. In this paper, an optimization model of mixture ...
IEEE

Parallelization of Revised Simplex Algorithm on GPUs

Abstract: This paper develops a novel Single Instruction Multiple Data (SIMD) Architecture processors (GPUs) based RSA algorithm and applies it to mass data processing on sensor network. The Intensive ...