A Verified High-Performance Composable Object Library for Remote Direct Memory Access (Extended Version)

2025-10-12

AI Summary

RDMA offers low latency and high throughput but suffers from a weak memory model lacking formal foundations, hindering the construction of correct, composable multi-node concurrent objects. Method: We introduce LOCO—the first RDMA-native multi-node object library supporting formal verification—bridging shared-memory and distributed programming paradigms. To address RDMA consistency modeling challenges, we design Mowgli, a modular, declarative verification framework that decouples proof logic from the memory model and enables systematic correctness proofs leveraging locality properties. Contribution/Results: LOCO achieves performance comparable to custom RDMA systems while drastically simplifying the programming model. All core components are fully formally verified. LOCO provides a high-reliability, high-performance infrastructure foundation for data centers, HPC, and AI/ML workloads.

Technology Category

• Machine Learning: Distributed Machine Learning & Federated Learning
• Data Mining & Knowledge Management: Scalability, Parallel & Distributed Systems
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Location- and context-aware Web and WoT applications and services
• Security and Privacy: Data transparency and provenance
• Search and Retrieval-Augmented AI: Retrieval-Augmented Generation (RAG) and multi-modal RAG

Abstract

Remote Direct Memory Access (RDMA) is a memory technology that allows remote devices to directly write to and read from each other's memory, bypassing components such as the CPU and operating system. This enables low-latency high-throughput networking, as required for many modern data centres, HPC applications and AI/ML workloads. However, baseline RDMA comprises a highly permissive weak memory model that is difficult to use in practice and has only recently been formalised. In this paper, we introduce the Library of Composable Objects (LOCO), a formally verified library for building multi-node objects on RDMA, filling the gap between shared memory and distributed system programming. LOCO objects are well-encapsulated and take advantage of the strong locality and the weak consistency characteristics of RDMA. They have performance comparable to custom RDMA systems (e.g. distributed maps), but with a far simpler programming model amenable to formal proofs of correctness. To support verification, we develop a novel modular declarative verification framework, called Mowgli, that is flexible enough to model multinode objects and is independent of a memory consistency model. We instantiate Mowgli with the RDMA memory model, and use it to verify correctness of LOCO libraries.

Problem

• Formally verifies composable objects for RDMA weak memory model
• Bridges shared memory and distributed system programming gaps
• Provides high-performance RDMA libraries with correctness proofs

Innovation

• Formally verified library for RDMA multi-node objects
• Modular declarative framework for distributed verification
• Encapsulated objects with strong locality weak consistency