Super-speeds with Zero-RAM: Next Generation Large-Scale Optimization in Your Laptop!

TL;DR

This paper introduces a groundbreaking general-purpose algorithm that enables large-scale optimization on laptops and embedded devices, achieving unprecedented speeds and efficiency with minimal memory usage.

Contribution

The paper presents a novel algorithm capable of solving billion-variable optimization problems efficiently on standard laptops, demonstrating linear computational and memory efficiency.

Findings

Solved Griewank function with 1 billion variables in ~18 hours

Uses only 7.6 GB RAM on a single-threaded CPU

Achieves linear speed and memory efficiency

Abstract

This article presents the novel breakthrough general purpose algorithm for large scale optimization problems. The novel algorithm is capable of achieving breakthrough speeds for very large-scale optimization on general purpose laptops and embedded systems. Application of the algorithm to the Griewank function was possible in up to 1 billion decision variables in double precision took only 64485 seconds (~18 hours) to solve, while consuming 7,630 MB (7.6 GB) or RAM on a single threaded laptop CPU. It shows that the algorithm is computationally and memory (space) linearly efficient, and can find the optimal or near-optimal solution in a fraction of the time and memory that many conventional algorithms require. It is envisaged that this will open up new possibilities of real-time large-scale problems on personal laptops and embedded systems.