標題: | High-Density Multiple Bits-per-Cell 1T4R RRAM Array with Gradual SET/RESET and its Effectiveness for Deep Learning |
作者: | Hsieh, E. R. Giordano, M. Hodson, B. Levy, A. Osekowsky, S. K. Radway, R. M. Shih, Y. C. Wan, W. Wu, T. F. Zheng, X. Nelson, M. Le, B. Q. Wong, H. -S. P. Mitra, S. Wong, S. 電子工程學系及電子研究所 Department of Electronics Engineering and Institute of Electronics |
公開日期: | 1-一月-2019 |
摘要: | We present the first demonstration of 1T4R Resistive RAM (RRAM) array storing two bits per RRAM cell. Our HfO2-based RRAM is built using a logic foundry technology that is fully compatible with the CMOS back-end process. We present a new approach to program RRAM cells using gradual SET/RESET pulses while minimizing disturbances on adjacent cells (belonging to the same 1T4R RRAM structure) this new approach makes pour multiple-bits-per-cell 1T4R RRAM array demonstration possible. We report over 106 cycles of endurance and a projected 10-year retention at 120 degrees C. Using measured data from our 2 bits-per-cell 1T4R RRAM array, we analyze multiple deep learning applications and demonstrate high degrees of inference accuracy (within 0.01% of ideal values). |
URI: | http://hdl.handle.net/11536/155249 |
ISBN: | 978-1-7281-4031-5 |
ISSN: | 2380-9248 |
期刊: | 2019 IEEE INTERNATIONAL ELECTRON DEVICES MEETING (IEDM) |
起始頁: | 0 |
結束頁: | 0 |
顯示於類別: | 會議論文 |