Dynamic Random Access Memory Modeling
Dynamic Random Access Memory Modeling is a computational framework that formally characterizes the behavior, performance, and reliability of dynamic random access memory systems by integrating temporal dynamics, charge leakage effects, and access patterns into predictive models for memory operation and optimization.
43
Publications
2.8K
Citations
164
Authors
42
Institutions
Publications per year
2017–2026
11
Variants
Dram Modeling
Parents
43
1–5 of 43
164
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42
University of Kaiserslautern
Kaiserslautern, Germany
5 h-index
21 publications
454 citations
Hitachi (Japan)
Tokyo, Japan
4 h-index
21 publications
444 citations
Seoul National University
Seoul, South Korea
3 h-index
7 publications
140 citations
Stanford University
Stanford, United States
2 h-index
2 publications
398 citations
Samsung (South Korea)
Seoul, South Korea
2 h-index
11 publications
225 citations
Fraunhofer Institute for Experimental Software Engineering
Kaiserslautern, Germany
2 h-index
2 publications
33 citations

National Yang Ming Chiao Tung University
Hsinchu, Taiwan
2 h-index
8 publications
191 citations
Korea Advanced Institute of Science and Technology
Daejeon, South Korea
2 h-index
2 publications
21 citations
1–8 of 42
2 publications · 37 citations
2
h-index
2 publications · 1.2K citations
2
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1 publications · 75 citations
1
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1 publications · 12 citations
1
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SMJ · 1 publications · 379 citations
1
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1–5