Hardware memory disaggregation is an emerging trend in datacenters that provides access to remote memory as part of a shared pool or unused memory on machines across the network. Memory disaggregation aims to improve memory utilization and scale memory-intensive applications. Current state-of-the-art prototypes have shown that hardware disaggregated memory is a reality at the rack-scale. However, the memory utilization benefits of memory disaggregation can only be fully realized at larger scales enabled by a datacenter-wide network. Introduction of a datacenter network results in new performance and reliability failures that may manifest as higher network latency. Additionally, sharing of the network introduces new points of contention between multiple applications. In this work, we characterize the impact of variable network latency and contention in an open-source hardware disaggregated memory prototype - ThymesisFlow. To support our characterization, we have developed a delay injection framework that introduces delays in remote memory access to emulate network latency. Based on the characterization results, we develop insights into how reliability and resource allocation mechanisms should evolve to support hardware memory disaggregation beyond rack-scale in datacenters.
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In-network Contention Resolution for Disaggregated Memory
Passive remote memory remains the holy grail of disaggregation. Most existing systems for disaggregated memory either use remote memory simply as a backing store, or design special-purpose data structures that require some amount of processing co-resident with the remote memory to manage and apply updates. The few proposals for truly passive remote memory perform well only with read-mostly workloads, rapidly deteriorating in the face of even low levels of write contention. We propose to leverage in-network devices (specifically, a programmable top-of-rack switch) to serialize remote memory accesses and resolve any write conflicts in flight. Our prototype is able to completely avoid write contention in the recently published Clover disaggregated key/value store, delivering a performance boost of almost 50% on our testbed under a mixed read/write workload.
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- Award ID(s):
- 1911104
- NSF-PAR ID:
- 10284128
- Date Published:
- Journal Name:
- Proceedings of the Workshop on Resource Disaggregation and Serverless (WORDS)
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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