Machine learning approach to multicore data structures

Abstract

In this study, a novel method for constructing self-aware data structures using online machine learning is proposed. This research introduced a novel category of data structures called Smart Data Structures, which continuously and automatically improve themselves to help simplify the complexity of manually modifying data structures for varied systems, applications, and workloads. This study also concluded that online machine learning is useful for autonomous data structure modification. For the online machine learning algorithm, I have proposed a reinforcement machine learning algorithm that benefits from the reward system and optimize the knobs accordingly. Online learning, in my opinion, offers a trustworthy and efficient framework for assessing intricate dynamic tradeoffs. Many of the possible difficulties that programmers may encounter in their daily work may be eliminated by using intelligent multicore data structures.