Name
Abstract | ||
|---|---|---|
Compute-in-memory (CIM) is a new computing paradigm that addresses the memory-wall problem in the deep learning accelerator. Resistive Random Access Memory (RRAM) is an emerging non-volatile memory that is suitable as on-chip embedded memory to store the weights of the deep neural network (DNN) models. In this paper, first we will review general design considerations of RRAM-CIM prototype chip int... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/AICAS51828.2021.9458481 | 2021 IEEE 3rd International Conference on Artificial Intelligence Circuits and Systems (AICAS) |
Keywords | DocType | ISBN |
Semiconductor device modeling,Runtime,Processor scheduling,Nonvolatile memory,Computational modeling,Resistive RAM,Prototypes | Conference | 978-1-6654-1913-0 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Anni Lu | 1 | 1 | 1.71 |
| Xiaochen Peng | 2 | 61 | 12.17 |
| Shimeng Yu | 3 | 490 | 56.22 |