Name
Abstract | ||
|---|---|---|
Since the redundancy analysis (RA) has been introduced for memory yield, many RA researches have been conducted. However, objective comparisons of them are difficult by the absence of real memory models with realistic fault distributions. This paper presents a fail memory configuration set for RA estimation, called as ITC'2020 RA Benchmarks. It enables objective estimations of RAs with respect to effectiveness and efficiency. The fail memory configuration set includes memory models which have various redundancy structures and a fault generation algorithm with fault distribution which can be criteria for objective comparisons of RA. Simulations for estimations and comparisons of RA researches including BIRA are progressed utilizing the fail memory configuration set. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/ITC44778.2020.9325273 | 2020 IEEE International Test Conference (ITC) |
Keywords | DocType | ISSN |
redundancy analysis (RA),built-in RA (BIRA),benchmark,memory model,fault distribution,redundancy structure,repair rate,analysis time | Conference | 1089-3539 |
ISBN | Citations | PageRank |
978-1-7281-9114-0 | 1 | 0.36 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hayoung Lee | 1 | 5 | 3.14 |
| Keewon Cho | 2 | 18 | 4.64 |
| Sungho Kang | 3 | 436 | 78.44 |
| Wooheon Kang | 4 | 1 | 0.36 |
| Seungtaek Lee | 5 | 2 | 1.05 |
| Woosik Jeong | 6 | 1 | 0.36 |