Reram-Based Machine Learning - Yu, Hao; Ni, Leibin; Pudukotai Dinakarrao, Sai Manoj
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Serving as a bridge between researchers in the computing domain and computing hardware designers, this book presents ReRAM techniques for distributed computing using IMC accelerators, ReRAM-based IMC architectures for machine learning (ML) and data-intensive applications, and strategies to map ML designs onto hardware accelerators.

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Produktbeschreibung
Serving as a bridge between researchers in the computing domain and computing hardware designers, this book presents ReRAM techniques for distributed computing using IMC accelerators, ReRAM-based IMC architectures for machine learning (ML) and data-intensive applications, and strategies to map ML designs onto hardware accelerators.
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Autorenporträt
Hao Yu is a professor in the School of Microelectronics at Southern University of Science and Technology (SUSTech), China. His main research interests cover energy-efficient IC chip design and mmwave IC design. He is a senior member of IEEE and a member of ACM. He has written several books and holds 20 granted patents. He is a distinguished lecturer of IEEE Circuits and Systems and associate editor of Elsevier Integration, the VLSI Journal, Elsevier Microelectronics Journal, Nature Scientific Reports, ACM Transactions on Embedded Computing Systems and IEEE Transactions on Biomedical Circuits and Systems. He is also a technical program committee member of several IC conferences, including IEEE CICC, BioCAS, A-SSCC, ACM DAC, DATE and ICCAD. He obtained his Ph.D. degree from the EE department at UCLA, USA.