# High-Performance Distributed RMA Locks

arXiv: https://arxiv.org/abs/2010.09854 · HTML: https://mlsanity.com/paper/2010.09854/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Oct 2020.

## Built on by (most cited first, 2 of 2)

- [Parallel and Distributed Graph Neural Networks: An In-Depth Concurrency Analysis](https://mlsanity.com/paper/2205.09702/) (2022)
- [GraphMineSuite: Enabling High-Performance and Programmable Graph Mining Algorithms with Set Algebra](https://mlsanity.com/paper/2103.03653/) (2021)

## Abstract (arXiv)

We propose a topology-aware distributed Reader-Writer lock that accelerates irregular workloads for supercomputers and data centers. The core idea behind the lock is a modular design that is an interplay of three distributed data structures: a counter of readers/writers in the critical section, a set of queues for ordering writers waiting for the lock, and a tree that binds all the queues and synchronizes writers with readers. Each structure is associated with a parameter for favoring either readers or writers, enabling adjustable performance that can be viewed as a point in a three dimensional parameter space. We also develop a distributed topology-aware MCS lock that is a building block of the above design and improves state-of-the-art MPI implementations. Both schemes use non-blocking Remote Memory Access (RMA) techniques for highest performance and scalability. We evaluate our schemes on a Cray XC30 and illustrate that they outperform state-of-the-art MPI-3 RMA locking protocols by 81% and 73%, respectively. Finally, we use them to accelerate a distributed hashtable that represents irregular workloads such as key-value stores or graph processing.