English

Spindle: Techniques for Optimizing Atomic Multicast on RDMA

Distributed, Parallel, and Cluster Computing 2023-10-10 v1

Abstract

Leveraging one-sided RDMA for applications that replicate small data objects can be surprisingly difficult: such uses amplify any protocol overheads. Spindle is a set of optimization techniques for systematically tackling this class of challenges for atomic multicast over RDMA. These include memory polling optimizations using novel sender and receiver batching techniques, null-message send logic, and improved multi-thread synchronization. We applied Spindle to Derecho, an open-source C++ library for atomic multicast, and obtained significant performance improvements both for the library itself and for an OMG-compliant avionics DDS built over Derecho. Derecho's multicast bandwidth utilization for 10KB messages rose from 1GB/s to 9.7GB/s on a 12.5GB/s network, and it became more robust to delays. Interestingly, although some of our techniques employ batching, latency dropped by nearly two orders of magnitude. Spindle optimizations should also be of value in other RDMA applications limited by the speed of coordination.

Keywords

Cite

@article{arxiv.2110.00886,
  title  = {Spindle: Techniques for Optimizing Atomic Multicast on RDMA},
  author = {Sagar Jha and Lorenzo Rosa and Ken Birman},
  journal= {arXiv preprint arXiv:2110.00886},
  year   = {2023}
}

Comments

14 pages including 1 page for references. To be submitted to an IEEE journal potentially

R2 v1 2026-06-24T06:34:46.484Z