| dc.contributor.author | Hao, Xiangpeng | |
| dc.contributor.author | Zhou, Xinjing | |
| dc.contributor.author | Yu, Xiangyao | |
| dc.contributor.author | Stonebraker, Michael | |
| dc.date.accessioned | 2024-04-04T16:21:03Z | |
| dc.date.available | 2024-04-04T16:21:03Z | |
| dc.date.issued | 2024-03-12 | |
| dc.identifier.issn | 2836-6573 | |
| dc.identifier.uri | https://hdl.handle.net/1721.1/154066 | |
| dc.description.abstract | The scaling of per-GB DRAM cost has slowed down in recent years. Recent research has suggested that adding remote memory to a system can further reduce the overall memory cost while maintaining good performance.
Remote memory (i.e., tiered memory), connected to host servers via high-speed interconnect protocols such as RDMA and CXL, is expected to deliver 100x (less than 1us) lower latency than SSD and be more cost-effective than local DRAM through pooling or adopting cheaper memory technologies.
Tiered memory opens up a large number of potential use cases within database systems. But previous work has only explored limited ways of using tiered memory. Our study provides a systematic study for DBMS to build tiered memory buffer management with respect to a wide range of hardware performance characteristics. Specifically, we study five different indexing designs that leverage remote memory in different ways and evaluate them through a wide range of metrics including performance, tiered-memory latency sensitivity, and cost-effectiveness.
In addition, we propose a new memory provisioning strategy that allocates an optimal amount of local and remote memory for a given workload. Our evaluations show that while some designs achieve higher performance than others, no design can win in all measured dimensions. | en_US |
| dc.publisher | Association for Computing Machinery | en_US |
| dc.relation.isversionof | 10.1145/3639286 | en_US |
| dc.rights | Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. | en_US |
| dc.source | ACM | en_US |
| dc.title | Towards Buffer Management with Tiered Main Memory | en_US |
| dc.type | Article | en_US |
| dc.identifier.citation | Xiangpeng Hao, Xinjing Zhou, Xiangyao Yu, and Michael Stonebraker. 2024. Towards Buffer Management
with Tiered Main Memory. Proc. ACM Manag. Data 2, 1 (SIGMOD), Article 31 (February 2024), 26 pages. | en_US |
| dc.contributor.department | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory | |
| dc.relation.journal | Proceedings of the ACM on Management of Data | en_US |
| dc.identifier.mitlicense | PUBLISHER_POLICY | |
| dc.eprint.version | Final published version | en_US |
| dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
| eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
| dc.date.updated | 2024-04-01T07:48:43Z | |
| dc.language.rfc3066 | en | |
| dc.rights.holder | The author(s) | |
| dspace.date.submission | 2024-04-01T07:48:43Z | |
| mit.journal.volume | 2 | en_US |
| mit.journal.issue | 1 | en_US |
| mit.license | PUBLISHER_POLICY | |
| mit.metadata.status | Authority Work and Publication Information Needed | en_US |