Exploiting Locality in Lease-Based Replicated Transactional Memory via Task Migration

TL;DR

Lilac-TM is a decentralized lease-based distributed transactional memory system that dynamically optimizes transaction placement to improve performance for data-local workloads without adding overhead for non-local workloads.

Contribution

It introduces a novel self-optimizing lease circulation scheme that dynamically decides whether to migrate transactions or acquire leases, enhancing locality-aware performance.

Findings

Significant performance improvements for data-local workloads.

No overhead incurred for non-data local workloads.

First locality-aware decentralized lease-based DSTM implementation.

Abstract

We present Lilac-TM, the first locality-aware Distributed Software Transactional Memory (DSTM) implementation. Lilac-TM is a fully decentralized lease-based replicated DSTM. It employs a novel self- optimizing lease circulation scheme based on the idea of dynamically determining whether to migrate transactions to the nodes that own the leases required for their validation, or to demand the acquisition of these leases by the node that originated the transaction. Our experimental evaluation establishes that Lilac-TM provides significant performance gains for distributed workloads exhibiting data locality, while typically incurring no overhead for non-data local workloads.