A Programming Model for Disaggregated Memory over CXL

2024-07-23

arXiv.org

AI Summary

To address the lack of a concurrency programming model ensuring data correctness and crash consistency in CXL-based disaggregated memory systems, this paper introduces CXL0—the first high-level programming model tailored for CXL. Our approach centers on three key contributions: (1) a formal operational semantics unifying memory sharing, persistence, and fault behaviors; (2) two general algorithmic transformation mechanisms—persistent linearization supporting partial failures, and a persistent algorithm restructuring framework resilient to full-system crashes; and (3) a prototype implementation of CXL0, including a hardware abstraction layer and preliminary performance evaluation. By bridging rigorous formal foundations with practical system design, CXL0 establishes the first theoretically sound and engineering-feasible foundation for building reliable concurrent programs on CXL platforms.

Technology Category

• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Cognitive Modeling & Cognitive Systems: Other Foundations of Cognitive Modeling & Systems
• Machine Learning: Hardware-aware ML

Application Category

• Security and Privacy: Data transparency and provenance
• Graph Algorithms and Modeling for the Web: Foundation models and LLMs for Web-related graphs
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments

Abstract

CXL (Compute Express Link) is an emerging open industry-standard interconnect between processing and memory devices that is expected to revolutionize the way systems are designed in the near future. It enables cache-coherent shared memory pools in a disaggregated fashion at unprecedented scales, allowing algorithms to interact with a variety of storage devices using simple loads and stores. Alongside unleashing unique opportunities for a wide range of applications, CXL introduces new challenges of data management and crash consistency. Alas, CXL lacks an adequate programming model, which makes reasoning about the correctness and expected behaviors of algorithms and systems on top of it nearly impossible. In this work, we present CXL0, the first programming model for concurrent programs running on top of CXL. We propose a high-level abstraction for CXL memory accesses and formally define operational semantics on top of that abstraction. We perform initial measurements that provide practical insight into CXL0. We provide a set of general transformations that adapt concurrent algorithms to the new disruptive technology. These transformations enhance linearizable algorithms with durability under a general partial-failure model. We provide an additional transformation for algorithms designed for persistent main memory and full-system crashes. We believe that this work will serve as a stepping stone for systems design and modeling on top of CXL, and support the development of future models as software and hardware evolve.

Problem

• CXL environment
• programming methods
• data correctness and reliability

Innovation

• CXL Programming Model
• Data Integrity
• Robustness and Compatibility