Zobrazeno 1 - 10
of 101
pro vyhledávání: '"YOUGUANG ZHANG"'
Autor:
Youguang Zhang, Yining Bai, Guanda Wang, Kun Zhang, Lei Chen, Georgios Ch. Sirakoulis, Yue Zhang, Zhenyi Zheng, Chenyu Lian, Jinkai Wang, Zhizhong Zhang
Publikováno v:
IEEE Transactions on Circuits and Systems I: Regular Papers. 68:1193-1205
The data transfer bottleneck in Von Neumann architecture owing to the separation between processor and memory hinders the development of high-performance computing. The computing in memory (CIM) concept is widely considered as a promising solution fo
Publikováno v:
IEEE Transactions on Magnetics. 57:1-4
In the era of big data, the memory wall between the processor and the memory as well as leakage current have become major bottlenecks of the traditional CMOS-based Von-Neumann computer architecture. Computing-in-memory (CiM) based on non-volatile mem
Autor:
Youguang Zhang, Ying Wang, Chao Wang, Deming Zhang, Bi Wu, Dijun Liu, Zhaohao Wang, Xiaobo Sharon Hu
Publikováno v:
IEEE Transactions on Circuits and Systems I: Regular Papers. 67:4660-4669
Continued scaling of Complementary Metal Oxide Semiconductor (CMOS) integrated circuit technology is slowing down due to physical limitations, while the static power of CMOS based memory is increasing as the transistors shrink. As an alternative memo
Autor:
Youguang Zhang, Zhizhong Zhang, Xiulong Wu, Yining Bai, Zhenyi Zheng, Jinkai Wang, Yue Zhang, Chenyu Lian, Kun Zhang, Kelian Lin, Sorin Cotofana, Lei Chen, Guanda Wang
Publikováno v:
IEEE Transactions on Circuits and Systems I: Regular Papers. 67:4247-4258
While spintronic memories, for example, spin transfer torque magnetic random access memory (STT-MRAM), have shown huge potential for building next-generation memory due to their attractive characteristics, the relatively large write latency and defic
Publikováno v:
IEEE Transactions on Electron Devices. 67:1460-1465
Spin-transfer torque magnetic random access memory (STT-MRAM) offers nonvolatility, good scalability, high speed, and low-power benefits. Multilevel cell (MLC) is an efficient technology to boost the storage density of the STT-MRAM. However, the conv
Autor:
Ying Wang, Pengcheng Dai, Weisheng Zhao, Youguang Zhang, Chao Wang, Jianlei Yang, Yuanqing Cheng, Bi Wu, Dijun Liu, Zhaohao Wang, Xiaobo Sharon Hu
Publikováno v:
IEEE Transactions on Circuits and Systems I: Regular Papers. 67:108-120
High capacity last-level caches (LLCs) are being used to help alleviate the growing speed gap between the processor and main memory. However, traditional CMOS based memory technologies (SRAM, DRAM, et al.) for such LLCs consume high static power. Non
Publikováno v:
IEEE Transactions on Very Large Scale Integration (VLSI) Systems. 27:2668-2679
Convolution neural networks (CNNs) have demonstrated superior capability in computer vision, speech recognition, autonomous driving, and so forth, which are opening up an artificial intelligence (AI) era. However, conventional CNNs require significan
Autor:
Xing Chen, Xichao Zhang, Wang Kang, Weisheng Zhao, Daoqian Zhu, Zhaohao Wang, Youguang Zhang, Yan Zhou, Bi Wu
Publikováno v:
ACM Journal on Emerging Technologies in Computing Systems. 16:1-17
Racetrack memory (RM), a new storage scheme in which information flows along a nanotrack, has been considered as a potential candidate for future high-density storage device instead of hard disk drive (HDD). The first RM technology, which was propose
Publikováno v:
IEEE Transactions on Very Large Scale Integration (VLSI) Systems. 27:2046-2059
Emerging nonvolatile memories (NVMs), including resistive RAM (RRAM), phase-change memory (PCM), and magnetic RAM (MRAM), have opened up new pathways for Computing-In-Memory (CIM). Those NVM technologies can achieve energy-efficient computational ope
Publikováno v:
ISCAS
With the surge in demand for data storage and processing in emerging applications, the traditional CMOS-based Von-Neumann architecture is facing challenges such as memory wall and static power consumption. In order to conquer the above-mentioned bott