Work

CXLfork: Fast Remote Fork over CXL Fabrics

Year: 2025

Type: conference-paper

Abstract: The shared and distributed memory capabilities of the emerging Compute Express Link (CXL) interconnect urge us to rethink the traditional interfaces of system software. In this paper, we explore one such interface: remote fork using CXL-attached shared memory for cluster-wide process cloning. We present CXLfork, a remote fork interface that realizes close to zero-serialization, zero-copy process cloning across nodes over CXL fabrics. CXLfork utilizes globally-shared CXL memory for cluster-wide deduplication of process states. It also enables fine-grained control of state tiering between local and CXL memory. We use CXLfork to develop CXL-porter, an efficient horizontal autoscaler for serverless functions deployed on CXL fabrics. CXLfork minimizes cold-start overhead without sacrificing local memory. CXLfork attains restore latency close to that of a local fork, outperforming state-of-practice by 2.26x on average, and reducing local memory consumption by 87% on average.

Source: ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS)

DOI: 10.1145/3676641.3715988

Authors: Chloe Alverti, Stratos Psomadakis, Burak Ocalan, Shashwat Jaiswal, Tianyin Xu, Josep Torrellas

Institutions: University of Illinois Urbana-Champaign, National Technical University of Athens

Language: English

Topic: Parallel Computing and Optimization Techniques

Subfield: Hardware and Architecture

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: hybrid

Funder: Universitas Brawijaya