Abstract
High-yield performance-efficient remapping architecture, repairing algorithms and redundancy analysis (HYPERA) are proposed for 2D memory. The proposed hypercube-based memory repair architecture consists of spare row-like subcubes with a modified ternary CAM with an address concentrator and a parallel sorter-like address concentrator. Generally, for an acceptable repair rate about 3% of spare subcubes and no more than 5% of hardware overhead are required. A modified Quine-McCluskey algorithm and the Essential Cube Pivoting algorithm are also developed for redundancy analysis. Almost 100% of repair rate can be obtained using only 32 equivalent rows under reasonable situations. Under less spare memory the repair rates of proposed approaches can be much higher than most results of previous work.
| Original language | English |
|---|---|
| Pages (from-to) | 1663-1676 |
| Number of pages | 14 |
| Journal | Science China Information Sciences |
| Volume | 54 |
| Issue number | 8 |
| DOIs | |
| Publication status | Published - 2011 Aug 1 |
Fingerprint
All Science Journal Classification (ASJC) codes
- Computer Science(all)
Cite this
}
High-yield performance-efficient redundancy analysis for 2D memory. / Huang, Tsung-Chu.
In: Science China Information Sciences, Vol. 54, No. 8, 01.08.2011, p. 1663-1676.Research output: Contribution to journal › Article
TY - JOUR
T1 - High-yield performance-efficient redundancy analysis for 2D memory
AU - Huang, Tsung-Chu
PY - 2011/8/1
Y1 - 2011/8/1
N2 - High-yield performance-efficient remapping architecture, repairing algorithms and redundancy analysis (HYPERA) are proposed for 2D memory. The proposed hypercube-based memory repair architecture consists of spare row-like subcubes with a modified ternary CAM with an address concentrator and a parallel sorter-like address concentrator. Generally, for an acceptable repair rate about 3% of spare subcubes and no more than 5% of hardware overhead are required. A modified Quine-McCluskey algorithm and the Essential Cube Pivoting algorithm are also developed for redundancy analysis. Almost 100% of repair rate can be obtained using only 32 equivalent rows under reasonable situations. Under less spare memory the repair rates of proposed approaches can be much higher than most results of previous work.
AB - High-yield performance-efficient remapping architecture, repairing algorithms and redundancy analysis (HYPERA) are proposed for 2D memory. The proposed hypercube-based memory repair architecture consists of spare row-like subcubes with a modified ternary CAM with an address concentrator and a parallel sorter-like address concentrator. Generally, for an acceptable repair rate about 3% of spare subcubes and no more than 5% of hardware overhead are required. A modified Quine-McCluskey algorithm and the Essential Cube Pivoting algorithm are also developed for redundancy analysis. Almost 100% of repair rate can be obtained using only 32 equivalent rows under reasonable situations. Under less spare memory the repair rates of proposed approaches can be much higher than most results of previous work.
UR - http://www.scopus.com/inward/record.url?scp=79960783132&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79960783132&partnerID=8YFLogxK
U2 - 10.1007/s11432-011-4357-x
DO - 10.1007/s11432-011-4357-x
M3 - Article
AN - SCOPUS:79960783132
VL - 54
SP - 1663
EP - 1676
JO - Science in China, Series F: Information Sciences
JF - Science in China, Series F: Information Sciences
SN - 1009-2757
IS - 8
ER -