Reconfigurable Architecture Design and Computing Techniques for Deep learning Algorithms

Erscheinungsjahr 2027
ISBN: 978-3-032-47229-8
Verlag: Springer

Buch, Englisch, 290 Seiten, Format (B × H): 155 mm x 235 mm

Reihe: Sustainable Artificial Intelligence-Powered Applications

This book extensively examines the characteristics of modern Field Programmable Gate Arrays (FPGAs), delving into design methodologies and showcasing successful real-world applications within the realm of Artificial Intelligence (AI). It provides a comprehensive overview of the spectrum of hardware options available for AI tasks, highlighting the inherent advantages of FPGAs. Furthermore, the book delves into contemporary FPGA Integrated Circuits (ICs) while emphasizing the synergy with software support.At its core, the book revolves around the central theme of leveraging FPGA's parallel processing capabilities to meet the substantial computational demands inherent to AI applications. This involves not only comprehensive hardware implementations but also the development of tailored hardware accelerators. The textbook offers a panoramic view of the subject matter, encompassing diverse domains such as technological foundations for AI deployment, FPGA capabilities, software tools, and a wide array of hardware solutions from various suppliers. Moreover, it provides insights into research-driven implementations aimed at motivating the AI community to embrace and explore the potential of FPGA technology.This book covers the entirety of machine learning accelerators, opening pathways for the creation and advancement of intelligent applications. It transcends a singular perspective, avoiding exclusive focus on reconfigurable architectures for signal and image processing applications.For researchers seeking a profound understanding of the intricacies involved in conceiving and developing AI, deep learning, and machine learning applications using the FPGA platform, this book serves as an indispensable resource. Its audience is diverse, encompassing researchers, industry experts, scientists, and postgraduate students operating within the fields of computer engineering, electronics, and electrical engineering. It holds particular significance for those specializing in VLSI and embedded systems, FPGA technology, as well as machine learning and deep learning, among other multidisciplinary projects within these domains.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

V, Govindaraj

Dhanasekar, S

Sagayam, K. Martin

Pandey, Digvijay

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Bildsignalverarbeitung
• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Signalverarbeitung
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik
• Geisteswissenschaften Architektur Ökologische Aspekte in der Architektur

Inhaltsverzeichnis

Implementation Digital Signal Processing applications using Reconfigurable Field Programmable Gate Arrays.- Parallel Computing in Deep Learning with Field Programmable Gate Arrays.

Über Autor(innen)

Dr. GOVINDARAJ. V Dr. V. Govindaraj currently serves as an Associate Professor in the Department of Electronics and Communication Engineering at KIT-Kalaignarkarunanidhi Institute of Technology, Coimbatore, Tamil Nadu. With over 16 years of academic experience, he has established himself as a dedicated researcher and educator specializing in VLSI Design, Low Power Testing, and Machine Learning Applications in Semiconductor Circuits. He has published more than 28 research papers in reputed SCI and Scopus-indexed journals. At present he is guiding 6 Research Acholars

Dr. S. DHANASEKAR received his Bachelor of Engineering degree in Electrical and Electronics Engineering from K.S.Rangasamy College of Technology, Erode, Tamilnadu, India in 2004 and received his M.S Degree in VLSI CAD from Manipal Centre for Information Sciences, MAHE, Manipal, Karnataka, India in 2006. He worked as R & D Engineer (VLSI and DSP Division) in Scientech Technologies Pvt. Ltd, Indore, Madhya Pradesh, India. He has completed his Ph.D. degree in Information and Communication Engineering from Anna University, Chennai, India in 2019. He is currently working as Associate Professor in Electronics and Communication Engineering, Sri Eshwar College of Engineering, Coimbatore, Tamilnadu.

Dr. K. MARTIN SAGAYAM is an accomplished academician and researcher in the Department of Electronics and Communication Engineering at Karunya Institute of Technology and Sciences, Coimbatore, India. He is listed among the Top 2% world scientists by Stanford University, USA, in recognition of his exceptional global research impact. He earned his Ph.D. in Pattern Recognition and Machine Learning Algorithms from Karunya University in 2018, following his M.E. in Communication Systems (First Class with Distinction, 2011) and B.E. in Electronics and Communication Engineering (First Class with Distinction, 2009) from Anna University, Chennai. He is currently pursuing postdoctoral research at Lincoln University, Malaysia, and as a Postdoctoral Research Fellow at the Federal University of Piaui, Brazil. Dr. Sagayam has an outstanding research record, with more than 155+ Scopus/SCI(E) indexed papers, including 50 SCIE articles, 12 books, and 36 books/chapters edited or authored with reputed publishers such as IGI Global, CRC Press, IET Publications, and Springer. His works have collectively earned a cumulative impact factor exceeding 156, with over 2833 citations and an h-index of 30, attesting to the influence of his research in global academia.

Dr. DIGVIJAY PANDEY is a distinguished academic and researcher in the field of Electronics Engineering, currently serving as a Senior Lecturer under the Department of Technical Education . Recognized among the world’s top 2% scientists by Stanford University for both 2024 and 2025, Dr. Pandey brings a wealth of expertise and dedication to technical education and research. He holds a Ph.D. in Electronics Engineering from Dr. A.P.J. Abdul Kalam Technical University, Lucknow, and a Master of Technology in Digital Systems and Design from Kamla Nehru Institute of Technology (KNIT), Sultanpur. His foundational engineering education was completed with a Bachelor of Technology in Electronics Engineering from the Institute of Engineering and Rural Technology (I.E.R.T.),

Dr. NGUYEN HA HUY CUONG academic journey is a testament to his dedication to excellence in computer science and related fields. He earned his Ph.D. in Computer Science from the Faculty of Information Technology, University of Science and Technology, University of Ðà N?ng (DUT-UDN), a leading institution in Vietnam known for its rigorous academic standards and contributions to technical education. His doctoral research focused on iCloud Computing, exploring innovative approaches to cloud-based systems and their applications in scalable, efficient technological solutions.