Name
Title | ||
|---|---|---|
Characterization and Mitigation of Relaxation Effects on Multi-level RRAM based In-Memory Computing |
Abstract | ||
|---|---|---|
In this paper, we investigate the relaxation effects on multi-level resistive random access memory (RRAM) based in-memory computing (IMC) for deep neural network (DNN) inference. We characterized 2-bit-per-cell RRAM IMC prototypes and measured the relaxation effects over 100 hours on multiple 8 kb test chips, where the relaxation is found to be most severe in the two intermediate states. We incorp... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/IRPS46558.2021.9405228 | 2021 IEEE International Reliability Physics Symposium (IRPS) |
Keywords | DocType | ISSN |
Training,Semiconductor device measurement,Neural networks,Resistive RAM,Prototypes,SPICE,Stability analysis | Conference | 1541-7026 |
ISBN | Citations | PageRank |
978-1-7281-6893-7 | 0 | 0.34 |
References | Authors | |
0 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wangxin He | 1 | 0 | 0.34 |
| Wonbo Shim | 2 | 1 | 1.69 |
| Shihui Yin | 3 | 71 | 10.03 |
| Xiaoyu Sun | 4 | 95 | 16.54 |
| Deliang Fan | 5 | 0 | 0.34 |
| Shimeng Yu | 6 | 5 | 1.94 |
| Jae-sun Seo | 7 | 536 | 56.32 |