A Verified High-Performance Composable Object Library for Remote Direct Memory Access
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.
Authors
- Gregory Chockler (ORCID: https://orcid.org/0000-0001-6700-9235)
- Guillaume Ambal (ORCID: https://orcid.org/0000-0002-4667-7266)
- Joseph Izraelevitz (ORCID: https://orcid.org/0009-0002-1267-5024)
- Azalea Raad (ORCID: https://orcid.org/0000-0002-2319-3242)
- Mark Madler
- Viktor Vafeiadis
- George Hodgkins
Institutions
- University of Colorado Boulder (US)
- University of Surrey (GB)
- Max Planck Institute for Software Systems (DE)
- Imperial College London (GB)
Publication Details
- Journal
- Proceedings of the ACM on Programming Languages
- Published
- 2026-01-08
- DOI
- https://doi.org/10.1145/3776713
- Primary Topic
- Distributed systems and fault tolerance
- Type
- article
- Field-Weighted Citation Impact
- 0.00