CAREER: Towards Learning-Based Storage Systems with Hardware-Software Co-Design

University Of Illinois At Urbana-Champaign, Urbana IL

Investigators

Abstract

Storage systems today have been built into a complicated ecosystem, which involves the development and deployment of storage devices, storage software, and application-level data stores. To rapidly meet the ever-increasing storage performance and efficiency requirements, the entire storage hardware and software stack need to adapt instantly in a coordinated fashion. However, it is challenging to achieve this with current human-driven systems-building approaches. Recent advancements in machine learning techniques show that the learning-based approach is a promising method to solve system optimization problems. However, it remains unclear how the storage ecosystem should be advanced to embrace the learning techniques to facilitate its development, deployment, and optimizations across the full stack. This project proposes to develop systems and architecture techniques to build a learning-based storage ecosystem. It has four major thrusts. First, the project proposes to enable the development of customized storage devices for specific application types with automated tuning of hardware specifications, therefore, we can enable developers to identify optimal device specifications with much less time and effort. Second, the project plans to develop elastic storage management for multi-tenant applications using reinforcement learning, thus, we can achieve both improved resource utilization and performance isolation. Third, the project proposes to integrate the storage hardware knowledge into the learning procedure to facilitate the development of learning-based storage software. Finally, the project will revisit the storage hardware architecture for building learning-based storage drives to further enhance the learning-based storage ecosystem. The project will facilitate the development of a new course that centers around memory and storage technologies. The project will also promote computer systems and architecture education to underrepresented and high school students through various research workshops and summer camps. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.