Affiliation:
1. Ghent University, Belgium
2. Vrije Universiteit Brussel, Belgium / Ghent University, Belgium
3. Google, USA
Abstract
Emerging Non-Volatile Memory (NVM) technologies offer high capacity and energy efficiency compared to DRAM, but suffer from limited write endurance and longer latencies. Prior work seeks the best of both technologies by combining DRAM and NVM in hybrid memories to attain low latency, high capacity, energy efficiency, and durability. Coarsegrained hardware and OS optimizations then spread writes out (wear-leveling) and place highly mutated pages in DRAM to extend NVM lifetimes. Unfortunately even with these coarse-grained methods, popular Java applications exact impractical NVM lifetimes of 4 years or less. This paper shows how to make hybrid memories practical, without changing the programming model, by enhancing garbage collection in managed language runtimes. We find object write behaviors offer two opportunities: (1) 70% of writes occur to newly allocated objects, and (2) 2% of objects capture 81% of writes to mature objects. We introduce writerationing garbage collectors that exploit these fine-grained behaviors. They extend NVM lifetimes by placing highly mutated objects in DRAM and read-mostly objects in NVM. We implement two such systems. (1) Kingsguard-nursery places new allocation in DRAM and survivors in NVM, reducing NVM writes by 5× versus NVM only with wear-leveling. (2) Kingsguard-writers (KG-W) places nursery objects in DRAM and survivors in a DRAM observer space. It monitors all mature object writes and moves unwritten mature objects from DRAM to NVM. Because most mature objects are unwritten, KG-W exploits NVM capacity while increasing NVM lifetimes by 11×. It reduces the energy-delay product by 32% over DRAM-only and 29% over NVM-only. This work opens up new avenues for making hybrid memories practical.
Funder
European Research Council
Publisher
Association for Computing Machinery (ACM)
Subject
Computer Graphics and Computer-Aided Design,Software
Cited by
8 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Reinvent Cloud Software Stacks for Resource Disaggregation;Journal of Computer Science and Technology;2023-09
2. MaPHeA: A Framework for Lightweight Memory Hierarchy-aware Profile-guided Heap Allocation;ACM Transactions on Embedded Computing Systems;2022-12-13
3. Challenges and future directions for energy, latency, and lifetime improvements in NVMs;Distributed and Parallel Databases;2022-09-21
4. FFCCD;Proceedings of the 49th Annual International Symposium on Computer Architecture;2022-06-11
5. Mako: a low-pause, high-throughput evacuating collector for memory-disaggregated datacenters;Proceedings of the 43rd ACM SIGPLAN International Conference on Programming Language Design and Implementation;2022-06-09