Active Access: A Mechanism for High-Performance Distributed Data-Centric Computations

TL;DR

Active Access (AA) integrates active messaging with RDMA to enable high-performance, data-centric distributed computations, improving performance and supporting new protocols in HPC systems.

Contribution

The paper introduces Active Access, a novel mechanism combining active messaging semantics with RDMA, supported by IOMMU extensions, to enhance distributed data-centric computation performance.

Findings

AA outperforms existing AM and RMA designs.

Accelerates distributed hashtables and logging schemes.

Enables new protocols like incremental checkpointing.

Abstract

Remote memory access (RMA) is an emerging high-performance programming model that uses RDMA hardware directly. Yet, accessing remote memories cannot invoke activities at the target which complicates implementation and limits performance of data-centric algorithms. We propose Active Access (AA), a mechanism that integrates well-known active messaging (AM) semantics with RMA to enable high-performance distributed data-centric computations. AA supports a new programming model where the user specifies handlers that are triggered when incoming puts and gets reference designated addresses. AA is based on a set of extensions to the Input/Output Memory Management Unit (IOMMU), a unit that provides high-performance hardware support for remapping I/O accesses to memory. We illustrate that AA outperforms existing AM and RMA designs, accelerates various codes such as distributed hashtables or logging schemes, and enables new protocols such as incremental checkpointing for RMA.We also discuss how extended IOMMUs can support a virtualized global address space in a distributed system that offers features known from on-node memory virtualization. We expect that AA can enhance the design of HPC operating and runtime systems in large computing centers.