Demo Data from EDBT 2026 / reviewers in the wild / expert
Liyin Liu
dblp:290/8424
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2021
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Hardware reliability and fault tolerance · 44% Memory systems · 44% Cloud and datacenter computing · 13% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Memory systems
DRAM |
0.5 | 1 | 2021 | CARE: Coordinated Augmentation for Elastic Resilience on DRAM Errors in Data Centers · HPCA 2021 |
Hardware reliability and fault tolerance › memory fault tolerance
DRAM fault tolerance |
0.5 | 1 | 2021 | CARE: Coordinated Augmentation for Elastic Resilience on DRAM Errors in Data Centers · HPCA 2021 |
Cloud and datacenter computing › datacenter operations
datacenter reliability |
0.1 | 1 | 2021 | CARE: Coordinated Augmentation for Elastic Resilience on DRAM Errors in Data Centers · HPCA 2021 |
Methods — techniques the papers use, named apart from their topics
proactive resilience · 0.5cache-like error tracking · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | CARE: Coordinated Augmentation for Elastic Resilience on DRAM Errors in Data CentersabstractAs the computation density and memory capacity continues to grow, DRAM errors have become the leading cause of server crashes and/or system failures in modern data centers. While myriads of techniques have been proposed to mitigate their impact on system reliability, these solutions either incur significant overhead on performance, power and memory capacity or require modifying multiple system components; hence, they are impractical to implement or deploy. This paper proposes CARE, a novel error tolerance framework for efficient and elastic resilience on DRAM errors. It introduces a cache-like structure in the memory controller for dynamic error tracking and proactive resilience enhancement to achieve high error tolerance economically and practically. Experiment results show that with around 58KB area overhead in the memory controller, CARE achieves near Chipkill reliability without any memory capacity penalty and incurs negligible performance overhead compared with the baseline SEC-DED systems. CARE provides an attractive alternative to enhance the reliability in data centers. Xiaowei Jiang, Liyin Liu, Huifeng Xu |
HPCA | 4 |