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| Title |
15.2 A 28nm 64Kb Inference-Training Two-Way Transpose Multibit 6T SRAM Compute-in-Memory Macro for AI Edge Chips
|
|---|---|
| Published by |
Institute of Electrical and Electronics Engineers (IEEE), February 2020
|
| DOI | 10.1109/isscc19947.2020.9062949 |
| Authors |
Jian-Wei Su, Xin Si, Yen-Chi Chou, Ting-Wei Chang, Wei-Hsing Huang, Yung-Ning Tu, Ruhui Liu, Pei-Jung Lu, Ta-Wei Liu, Jing-Hong Wang, Zhixiao Zhang, Hongwu Jiang, Shanshi Huang, Chung-Chuan Lo, Ren-Shuo Liu, Chih-Cheng Hsieh, Kea-Tiong Tang, Shyh-Shyuan Sheu, Sih-Han Li, Heng-Yuan Lee, Shih-Chieh Chang, Shimeng Yu, Meng-Fan Chang |
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Mendeley demographics
The data shown below were compiled from readership statistics for 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 75 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 9 | 12% |
| Student > Bachelor | 7 | 9% |
| Student > Master | 7 | 9% |
| Lecturer | 3 | 4% |
| Other | 2 | 3% |
| Other | 4 | 5% |
| Unknown | 43 | 57% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 21 | 28% |
| Computer Science | 7 | 9% |
| Physics and Astronomy | 2 | 3% |
| Business, Management and Accounting | 1 | 1% |
| Energy | 1 | 1% |
| Other | 0 | 0% |
| Unknown | 43 | 57% |