VLDB 2026 Research / reviewers in the wild / expert
Kinshuk Chowdhury
dblp:24/6415
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2008
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 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 |
Electronic design automation · 46% Memory systems · 23% Hardware reliability and fault tolerance · 23% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Electronic design automation
hardware verification and test |
0.1 | 1 | 2008 | A methodology for statistical estimation of read access yield in SRAMs · DAC 2008 |
Hardware reliability and fault tolerance
process variation and yield analysis |
0.1 | 1 | 2008 | A methodology for statistical estimation of read access yield in SRAMs · DAC 2008 |
Memory systems › random-access memory
SRAM |
0.1 | 1 | 2008 | A methodology for statistical estimation of read access yield in SRAMs · DAC 2008 |
Electronic design automation
yield analysis |
0.1 | 1 | 2008 | A methodology for statistical estimation of read access yield in SRAMs · DAC 2008 |
Integrated circuit design
low-power circuit design |
0.0 | 1 | 2008 | A methodology for statistical estimation of read access yield in SRAMs · DAC 2008 |
Methods — techniques the papers use, named apart from their topics
statistical simulation · 0.1monte carlo · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2008 | A methodology for statistical estimation of read access yield in SRAMsabstractThe increase of process variations in advanced CMOS technologies is considered one of the biggest challenges for SRAM designers. This is aggravated by the strong demand for lower cost and power consumption, higher performance and density which complicates SRAM design process. In this paper, we present a methodology for statistical simulation of SRAM read access yield, which is tightly related to SRAM performance and power consumption. The proposed flow enables early SRAM yield predication and performance/power optimization in the design time, which is important for SRAM in nanometer technologies. The methodology is verified using measured silicon yield data from a 1 Mb memory fabricated in an industrial 45nm technology. Mohamed H. Abu-Rahma, Kinshuk Chowdhury, Sei Seung Yoon, Mohab Anis |
DAC | 2 |