Demo Data from VLDB 2026 / reviewers in the wild / expert
Sungkap Yeo
dblp:17/9999
· DBLP profile ↗
2ranked-venue papers
1as first author
0since 2021 · last 2014
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 2 · 1 first-authorSoftware engineering, systems software and programming languages · 1
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 |
Memory systems · 92% Hardware reliability and fault tolerance · 8% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Memory systems › non-volatile memory
multi-level cell |
0.2 | 1 | 2013 | Tri-level-cell phase change memory: toward an efficient and reliable memory system · ISCA 2013 |
Memory systems
non-volatile memory |
0.2 | 1 | 2013 | Tri-level-cell phase change memory: toward an efficient and reliable memory system · ISCA 2013 |
Memory systems › non-volatile memory
phase change memory |
0.2 | 1 | 2013 | Tri-level-cell phase change memory: toward an efficient and reliable memory system · ISCA 2013 |
Memory systems › emerging memory technologies
resistance drift |
0.0 | 1 | 2013 | Tri-level-cell phase change memory: toward an efficient and reliable memory system · ISCA 2013 |
Hardware reliability and fault tolerance
soft errors |
0.0 | 1 | 2013 | Tri-level-cell phase change memory: toward an efficient and reliable memory system · ISCA 2013 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | ATAC: Ambient Temperature-Aware Capping for Power Efficient DatacentersabstractThe emergence of cloud computing has created a demand for more datacenters, which in turn, has led to the substantial consumption of electricity by computing systems and cooling units. Although recently built warehouse-scale datacenters can nearly completely eliminate cooling overhead, small to medium datacenters, which still spend nearly half of their power on cooling, still labor under heavy cooling overhead. Often overlooked by the cloud computing community, these types of datacenters are not in the minority: They are responsible for more than 70% of the entire electrical power used by datacenters. Thus, to tackle the cooling inefficiencies of these datacenters, we propose ambient temperature-aware capping (ATAC), which maximizes power efficiency while minimizing overheating. ATAC senses the ambient temperature of each server and triggers a new performance capping mechanism to achieve 38% savings in cooling power and 7% savings in total power with less than 1% degradation in performance. Sungkap Yeo, Mohammad M. Hossain, Jen-Cheng Huang, Hsien-Hsin S. Lee |
SoCC | 1 |
| 2013 | Tri-level-cell phase change memory: toward an efficient and reliable memory systemabstractThere are several emerging memory technologies looming on the horizon to compensate the physical scaling challenges of DRAM. Phase change memory (PCM) is one such candidate proposed for being part of the main memory in computing systems. One salient feature of PCM is its multi-level-cell (MLC) property, which can be used to multiply the memory capacity at the cell level. However, due to the nature of PCM that the value written to the cell can drift over time, PCM is prone to a unique type of soft errors, posing a great challenge for their practical deployment. This paper first quantitatively studied the current art for MLC PCM in dealing with the resistance drift problem and showed that the previously proposed techniques such as scrubbing or error correction mechanisms have significant reliability challenges to overcome. We then propose tri-level-cell PCM and demonstrate its ability to achieving 105 x lower soft error rate than four-level-cell PCM and 1.33 x higher information density than single-level-cell PCM. According to our findings, the tri-level-cell PCM shows 36.4% performance improvement over the four-level-cell PCM while achieving the soft error rate of DRAM. Nak Hee Seong, Sungkap Yeo, Hsien-Hsin S. Lee |
ISCA | 2 |