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

职业：通过软硬件协同设计实现基于学习的存储系统

• 批准号: 2144796
• 负责人: Jian Huang
• 金额: $ 59.34万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-03-01 至 2027-02-28
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2144796&HistoricalAwards=false
• 关键词: CAREER; Towards; Learning; Based; Storage

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.

当今的存储系统已经构建成一个复杂的生态系统，其中涉及存储设备、存储软件和应用程序级数据存储的开发和部署。为了快速满足不断增长的存储性能和效率要求，整个存储硬件和软件堆栈需要以协调的方式立即适应。然而，这是具有挑战性的，以实现这一点与目前的人为驱动的系统建设方法。机器学习技术的最新进展表明，基于学习的方法是解决系统优化问题的一种很有前途的方法。然而，目前尚不清楚存储生态系统应如何推进，以采用学习技术来促进其整个堆栈的开发，部署和优化。该项目建议开发系统和架构技术，以构建基于学习的存储生态系统。它有四个主要的推力。首先，该项目建议为特定应用类型开发定制的存储设备，并自动调整硬件规格，因此，我们可以使开发人员以更少的时间和精力确定最佳的设备规格。其次，该项目计划使用强化学习为多租户应用程序开发弹性存储管理，从而实现提高资源利用率和性能隔离。第三，该项目建议将存储硬件知识集成到学习过程中，以促进基于学习的存储软件的开发。最后，该项目将重新审视构建基于学习的存储驱动器的存储硬件架构，以进一步增强基于学习的存储生态系统。该项目将促进围绕内存和存储技术的新课程的开发。该项目还将通过各种研究讲习班和夏令营促进计算机系统和建筑教育，以代表性不足和高中学生。该奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

项目成果

G10: Enabling An Efficient Unified GPU Memory and Storage Architecture with Smart Tensor Migrations

• DOI: 10.1145/3613424.3614309
• 发表时间: 2023-10
• 期刊: 2023 56th IEEE/ACM International Symposium on Microarchitecture (MICRO)
• 作者: Haoyang Zhang;Yirui Eric Zhou;Yu Xue;Yiqi Liu;Jian Huang

Learning to Drive Software-Defined Solid-State Drives

学习驱动软件定义的固态硬盘

• DOI: 10.1145/3613424.3614281
• 发表时间: 2023
• 期刊: Proceedings of the 56th Annual IEEE/ACM International Symposium on Microarchitecture
• 作者: Li, Daixuan;Sun, Jinghan;Huang, Jian
• 通讯作者: Huang, Jian

LeaFTL: A Learning-Based Flash Translation Layer for Solid-State Drives

• DOI: 10.1145/3575693.3575744
• 发表时间: 2022-12
• 期刊: Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 2
• 作者: Jinghan Sun;Shaobo Li-;Yunxin Sun;Chao Sun;D. Vučinić;Jian Huang

BlockFlex: Enabling Storage Harvesting with Software-Defined Flash in Modern Cloud Platforms

• 发表时间: 2022
• 作者: Benjamin Reidys;Jinghan Sun;Anirudh Badam;S. Noghabi;Jian Huang

Learning to Drive Software-Defined Storage

• 发表时间: 2022
• 作者: Jian Huang;Daixuan Li;Jinghan Sun