Name
Title | ||
|---|---|---|
Exploring the opportunity of implementing neuromorphic computing systems with spintronic devices |
Abstract | ||
|---|---|---|
Many cognitive algorithms such as neural networks cannot be efficiently executed by von Neumann architectures, the performance of which is constrained by the memory wall between microprocessor and memory hierarchy. Hence, researchers started to investigate new computing paradigms such as neuromorphic computing that can adapt their structure to the topology of the algorithms and accelerate their executions. New computing units have been also invented to support this effort by leveraging emerging nano-devices. In this work, we will discuss the opportunity of implementing neuromorphic computing systems with spintronic devices. We will also provide insights on how spintronic devices fit into different part of neuromorphic computing systems. Approaches to optimize the circuits are also discussed. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.23919/DATE.2018.8341988 | 2018 Design, Automation & Test in Europe Conference & Exhibition (DATE) |
Keywords | Field | DocType |
neuromorphic computing systems,spintronic devices,cognitive algorithms,von Neumann architectures,memory wall,microprocessor,memory hierarchy,computing paradigms,new computing units,emerging nanodevices | Memory wall,Computer architecture,Memory hierarchy,Computer science,Parallel computing,Microprocessor,Neuromorphic engineering,Non-volatile memory,Artificial neural network,Von Neumann architecture | Conference |
ISSN | Citations | PageRank |
1530-1591 | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bonan Yan | 1 | 76 | 9.47 |
| Fan Chen | 2 | 116 | 19.33 |
| Yaojun Zhang | 3 | 300 | 19.42 |
| Chang Song | 4 | 17 | 2.57 |
| Hai Li | 5 | 2435 | 208.37 |
| Yiran Chen | 6 | 3344 | 259.09 |