Demo Data from EDBT 2026 / reviewers in the wild / expert
Gyo-Young Jin
dblp:50/6013
· DBLP profile ↗
2ranked-venue papers
1as first author
0since 2021 · last 2017
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 2 · 1 first-author
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
2 papers |
Hardware reliability and fault tolerance · 53% Memory systems · 46% Electronic design automation · 1% |
Topics — the 8 heaviest of 8, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Memory systems
DRAM |
0.3 | 1 | 2017 | Defect Analysis and Cost-Effective Resilience Architecture for Future DRAM Devices · HPCA 2017 |
Hardware reliability and fault tolerance › memory fault tolerance
DRAM resilience |
0.3 | 1 | 2017 | Defect Analysis and Cost-Effective Resilience Architecture for Future DRAM Devices · HPCA 2017 |
Memory systems › DRAM
DRAM scaling |
0.3 | 1 | 2017 | Defect Analysis and Cost-Effective Resilience Architecture for Future DRAM Devices · HPCA 2017 |
Hardware reliability and fault tolerance › error correction › error-correcting codes
in-DRAM ECC |
0.3 | 1 | 2017 | Defect Analysis and Cost-Effective Resilience Architecture for Future DRAM Devices · HPCA 2017 |
Hardware reliability and fault tolerance › error-correcting codes for memory
rank-level ECC |
0.1 | 1 | 2017 | Defect Analysis and Cost-Effective Resilience Architecture for Future DRAM Devices · HPCA 2017 |
Electronic design automation › technology computer-aided design
device simulation |
0.0 | 1 | 1991 | Mixed particle Monte Carlo method for deep submicron semiconductor device simulator · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 1991 |
Integrated circuit design › semiconductor device modeling
drift-diffusion model |
0.0 | 1 | 1991 | Mixed particle Monte Carlo method for deep submicron semiconductor device simulator · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 1991 |
Integrated circuit design
semiconductor device modeling |
0.0 | 1 | 1991 | Mixed particle Monte Carlo method for deep submicron semiconductor device simulator · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 1991 |
Methods — techniques the papers use, named apart from their topics
simulation · 0.3measurement · 0.3monte carlo · 0.0langevin equation · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2017 | Defect Analysis and Cost-Effective Resilience Architecture for Future DRAM DevicesabstractTechnology scaling has continuously improved the density, performance, energy efficiency, and cost of DRAM-based main memory systems. Starting from sub-20nm processes, however, the industry began to pay considerably higher costs to screen and manage notably increasing defective cells. The traditional technique, which replaces the rows/columns containing faulty cells with spare rows/columns, has been able to cost-effectively repair the defective cells so far, but it will become unaffordable soon because an excessive number of spare rows/columns are required to manage the increasing number of defective cells. This necessitates a synergistic application of an alternative resilience technique such as In-DRAM ECC with the traditional one. Through extensive measurement and simulation, we first identify that aggressive miniaturization makes DRAM cells more sensitive to random telegraph noise or variable retention time, which is dominantly manifested as a surge in randomly scattered single-cell faults. Second, we advocate using InDRAM ECC to overcome the DRAM scaling challenges and architect In-DRAM ECC to accomplish high area efficiency and minimal performance degradation. Moreover, we show that advancement in process technology reduces decoding/correction time to a small fraction of DRAM access time, and that the throughput penalty of a write operation due to an additional read for a parity update is mostly overcome by the multi-bank structure and long burst writes that span an entire In-DRAM ECC codeword. Lastly, we demonstrate that system reliability with modern rank-level ECC schemes such as single device data correction is further improved by hundred million times with the proposed In-DRAM ECC architecture. Sang-uhn Cha, Seongil O, Hyunsung Shin, Sangjoon Hwang 0001, Kwang-Il Park, Seong-Jin Jang 0002, Joo-Sun Choi, Gyo-Young Jin, Young Hoon Son, Hyunyoon Cho, Jung Ho Ahn, Nam Sung Kim |
HPCA | 8 |
| 1991 | Mixed particle Monte Carlo method for deep submicron semiconductor device simulatorabstractA particle simulation method is introduced in which two kinds of particle models are used in one device. A conventional Monte Carlo particle model is used in the region where nonstatic effects are evident, and a particle model based on Langevin's equation is used in the region where the drift-diffusion approximation is valid. In this way it is possible to obtain efficiency and the required physical accuracy in device simulation. For the validity of this scheme, a silicon n/sup +/-n-n/sup +/ structure is simulated, and some important results are presented.> Gyo-Young Jin, Young-June Park, Hong-Shick Min |
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. | 1 |