MIND
| Autor: | Abhishek Bhattacharjee, Yupeng Tang, Anurag Khandelwal, Seung-seob Lee, Lin Zhong, Yanpeng Yu |
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| Rok vydání: | 2021 |
| Předmět: |
FOS: Computer and information sciences
Memory coherence Hardware_MEMORYSTRUCTURES business.product_category Computer science Distributed computing Memory management unit Memory management Resource (project management) Elasticity (cloud computing) Computer Science - Distributed Parallel and Cluster Computing Shared memory Network switch Distributed Parallel and Cluster Computing (cs.DC) business Cache coherence |
| Zdroj: | SOSP |
| DOI: | 10.1145/3477132.3483561 |
| Popis: | Memory-compute disaggregation promises transparent elasticity, high utilization and balanced usage for resources in data centers by physically separating memory and compute into network-attached resource "blades". However, existing designs achieve performance at the cost of resource elasticity, restricting memory sharing to a single compute blade to avoid costly memory coherence traffic over the network. In this work, we show that emerging programmable network switches can enable an efficient shared memory abstraction for disaggregated architectures by placing memory management logic in the network fabric. We find that centralizing memory management in the network permits bandwidth and latency-efficient realization of in-network cache coherence protocols, while programmable switch ASICs support other memory management logic at line-rate. We realize these insights into MIND, an in-network memory management unit for rack-scale memory disaggregation. MIND enables transparent resource elasticity while matching the performance of prior memory disaggregation proposals for real-world workloads. Comment: 18 pages, 9 figures, 2 tables |
| Databáze: | OpenAIRE |
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