Name
Abstract | ||
|---|---|---|
Compute-in-memory (CIM) is an attractive solution to process the extensive workloads of multiply-and-accumulate (MAC) operations in deep neural network (DNN) hardware accelerators. A simulator with options of various mainstream and emerging memory technologies, architectures and networks can be a great convenience for fast early-stage design space exploration of CIM accelerators. DNN+NeuroSim is a... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/AICAS51828.2021.9458501 | 2021 IEEE 3rd International Conference on Artificial Intelligence Circuits and Systems (AICAS) |
Keywords | DocType | ISBN |
Semiconductor device modeling,Wiring,Computational modeling,Wires,Predictive models,Common Information Model (computing),Calibration | Conference | 978-1-6654-1913-0 |
Citations | PageRank | References |
1 | 0.35 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Anni Lu | 1 | 1 | 1.71 |
| Xiaochen Peng | 2 | 61 | 12.17 |
| Wantong Li | 3 | 7 | 3.85 |
| Hongwu Jiang | 4 | 16 | 6.77 |
| Shimeng Yu | 5 | 490 | 56.22 |