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OverviewFull Product DetailsAuthor: Hao Yu (Professor, Southern University of Science and Technology (SUSTech), School of Microelectronics, China) , Leibin Ni (Principle Engineer, Huawei Technologies, Shenzhen, China) , Sai Manoj Pudukotai Dinakarrao (Assistant Professor, George Mason University (GMU), Department of Electrical and Computer Engineering, USA)Publisher: Institution of Engineering and Technology Imprint: Institution of Engineering and Technology ISBN: 9781839530814ISBN 10: 1839530812 Pages: 261 Publication Date: 30 April 2021 Audience: College/higher education , Professional and scholarly , Tertiary & Higher Education , Professional & Vocational Format: Hardback Publisher's Status: Active Availability: In Print ![]() This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us. Table of ContentsPart I: Introduction Chapter 1: Introduction Chapter 2: The need of in-memory computing Chapter 3: The background of ReRAM devices Part II: Machine learning accelerators Chapter 4: The background of machine learning algorithms Chapter 5: XIMA: the in-ReRAM machine learning architecture Chapter 6: The mapping of machine learning algorithms on XIMA Part III: Case studies Chapter 7: Large-scale case study: accelerator for ResNet Chapter 8: Large-scale case study: accelerator for compressive sensing Chapter 9: Conclusions: wrap-up, open questions and challengesReviewsAuthor InformationHao 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. Leibin Ni is a Principle engineer at Huawei Technologies, Shenzhen, China. His research interests include emerging nonvolatile memory platforms, computing in-memory architecture, machine learning applications and low power designs. He is a member of IEEE. He received his Ph.D. from the Nanyang Technological University, Singapore. Sai Manoj Pudukotai Dinakarrao is an assistant professor in the Department of Electrical and Computer Engineering at George Mason University (GMU), USA. His current research interests include hardware security, adversarial machine learning, Internet of things networks, deep learning in resource-constrained environments, in-memory computing, accelerator design, algorithms, design of self-aware many-core microprocessors and resource management in many-core microprocessors. He is a member of IEEE and ACM. He served as a guest editor to IEEE Design and Test Magazine and reviewer for multiple IEEE and ACM journals. Also, he is a technical program committee member of several CAD conferences, including ACM DAC, DATE, ICCAD, ASP-DAC, ESWEEK and many more. He received a Ph.D. degree in Electrical and Electronic Engineering from the Nanyang Technological University, Singapore. Tab Content 6Author Website:Countries AvailableAll regions |