ARTIFICIAL INTELLIGENCE APPLICATIONS and RECONFIGURABLE ARCHITECTURES The primary goal of this book is to present the design, implementation, and performance issues of AI applications and the suitability of the FPGA platform. This book covers the features of modern Field Programmable Gate Arrays (FPGA) devices, design techniques, and successful implementations pertaining to AI applications. It describes various hardware options available for AI applications, key advantages of FPGAs, and contemporary FPGA ICs with software support. The focus is on exploiting parallelism offered by FPGA to meet heavy computation requirements of AI as complete hardware implementation or customized hardware accelerators. This is a comprehensive textbook on the subject covering a broad array of topics like technological platforms for the implementation of AI, capabilities of FPGA, suppliers’ software tools and hardware boards, and discussion of implementations done by researchers to encourage the AI community to use and experiment with FPGA. Readers will benefit from reading this book because It serves all levels of students and researcher’s as it deals with the basics and minute details of Ecosystem Development Requirements for Intelligent applications with reconfigurable architectures whereas current competitors’ books are more suitable for understanding only reconfigurable architectures. It focuses on all aspects of machine learning accelerators for the design and development of intelligent applications and not on a single perspective such as only on reconfigurable architectures for IoT applications. It is the best solution for researchers to understand how to design and develop various AI, deep learning, and machine learning applications on the FPGA platform. It is the best solution for all types of learners to get complete knowledge of why reconfigurable architectures are important for implementing AI-ML applications with heavy computations. Audience Researchers, industrial experts, scientists, and postgraduate students who are working in the fields of computer engineering, electronics, and electrical engineering, especially those specializing in VLSI and embedded systems, FPGA, artificial intelligence, Internet of Things, and related multidisciplinary projects.

This book constitutes the proceedings of the 14th International Conference on Applied Reconfigurable Computing, ARC 2018, held in Santorini, Greece, in May 2018. The 29 full papers and 22 short presented in this volume were carefully reviewed and selected from 78 submissions. In addition, the volume contains 9 contributions from research projects. The papers were organized in topical sections named: machine learning and neural networks; FPGA-based design and CGRA optimizations; applications and surveys; fault-tolerance, security and communication architectures; reconfigurable and adaptive architectures; design methods and fast prototyping; FPGA-based design and applications; and special session: research projects.

EXPLAINABLE MACHINE LEARNING MODELS AND ARCHITECTURES This cutting-edge new volume covers the hardware architecture implementation, the software implementation approach, and the efficient hardware of machine learning applications. Machine learning and deep learning modules are now an integral part of many smart and automated systems where signal processing is performed at different levels. Signal processing in the form of text, images, or video needs large data computational operations at the desired data rate and accuracy. Large data requires more use of integrated circuit (IC) area with embedded bulk memories that further lead to more IC area. Trade-offs between power consumption, delay and IC area are always a concern of designers and researchers. New hardware architectures and accelerators are needed to explore and experiment with efficient machine-learning models. Many real-time applications like the processing of biomedical data in healthcare, smart transportation, satellite image analysis, and IoT-enabled systems have a lot of scope for improvements in terms of accuracy, speed, computational powers, and overall power consumption. This book deals with the efficient machine and deep learning models that support high-speed processors with reconfigurable architectures like graphic processing units (GPUs) and field programmable gate arrays (FPGAs), or any hybrid system. Whether for the veteran engineer or scientist working in the field or laboratory, or the student or academic, this is a must-have for any library.

This work is a comprehensive study of the field. It provides an entry point to the novice willing to move in the research field reconfigurable computing, FPGA and system on programmable chip design. The book can also be used as teaching reference for a graduate course in computer engineering, or as reference to advance electrical and computer engineers. It provides a very strong theoretical and practical background to the field, from the early Estrin’s machine to the very modern architecture such as embedded logic devices.

This book constitutes the refereed proceedings of the Third International Workshop on Applied Reconfigurable Computing, ARC 2007, held in Mangaratiba, Brazil, in March 2007. The 27 full papers and 10 short papers presented together with a late-comer contribution from ARC 2006 are organized in topical sections on architectures, mapping techniques and tools, arithmetic, and applications.

New Algorithms, Architectures and Applications for Reconfigurable Computing consists of a collection of contributions from the authors of some of the best papers from the Field Programmable Logic conference (FPL’03) and the Design and Test Europe conference (DATE’03). In all, seventy-nine authors, from research teams from all over the world, were invited to present their latest research in the extended format permitted by this special volume. The result is a valuable book that is a unique record of the state of the art in research into field programmable logic and reconfigurable computing. The contributions are organized into twenty-four chapters and are grouped into three main categories: architectures, tools and applications. Within these three broad areas the most strongly represented themes are coarse-grained architectures; dynamically reconfigurable and multi-context architectures; tools for coarse-grained and reconfigurable architectures; networking, security and encryption applications. Field programmable logic and reconfigurable computing are exciting research disciplines that span the traditional boundaries of electronic engineering and computer science. When the skills of both research communities are combined to address the challenges of a single research discipline they serve as a catalyst for innovative research. The work reported in the chapters of this book captures that spirit of that innovation.

Dynamic Reconfiguration: Architectures and Algorithms offers a comprehensive treatment of dynamically reconfigurable computer architectures and algorithms for them. The coverage is broad starting from fundamental algorithmic techniques, ranging across algorithms for a wide array of problems and applications, to simulations between models. The presentation employs a single reconfigurable model (the reconfigurable mesh) for most algorithms, to enable the reader to distill key ideas without the cumbersome details of a myriad of models. In addition to algorithms, the book discusses topics that provide a better understanding of dynamic reconfiguration such as scalability and computational power, and more recent advances such as optical models, run-time reconfiguration (on FPGA and related platforms), and implementing dynamic reconfiguration. The book, featuring many examples and a large set of exercises, is an excellent textbook or reference for a graduate course. It is also a useful reference to researchers and system developers in the area.

Zusammenfassung: The 7-volume set LNCS 14832 - 14838 constitutes the proceedings of the 24th International Conference on Computational Science, ICCS 2024, which took place in Malaga, Spain, during July 2-4, 2024. The 155 full papers and 70 short papers included in these proceedings were carefully reviewed and selected from 430 submissions. They were organized in topical sections as follows: Part I: ICCS 2024 Main Track Full Papers; Part II: ICCS 2024 Main Track Full Papers; Part III: ICCS 2024 Main Track Short Papers; Advances in High-Performance Computational Earth Sciences: Numerical Methods, Frameworks and Applications; Artificial Intelligence and High-Performance Computing for Advanced Simulations; Part IV: Biomedical and Bioinformatics Challenges for Computer Science; Computational Health; Part V: Computational Optimization, Modelling, and Simulation; Generative AI and Large Language Models (LLMs) in Advancing Computational Medicine; Machine Learning and Data Assimilation for Dynamical Systems; Multiscale Modelling and Simulation; Part VI: Network Models and Analysis: From Foundations to Artificial Intelligence; Numerical Algorithms and Computer Arithmetic for Computational Science; Quantum Computing; Part VII: Simulations of Flow and Transport: Modeling, Algorithms and Computation; Smart Systems: Bringing Together Computer Vision, Sensor Networks, and Artificial Intelligence; Solving Problems with Uncertainties; Teaching Computational Science

This book constitutes the thoroughly refereed conference proceedings of the 9th International Symposium on Reconfigurable Computing: Architectures, Tools and Applications, ARC 2013, held in Los Angeles, CA, USA, in March 2013. The 28 revised papers presented, consisting of 20 full papers and 11 poster papers were carefully selected from 41 submissions. The topics covered are applications, arithmetic, design optimization for FPGAs, architectures, place and routing.

This book constitutes the thoroughly refereed post-proceedings of the Second International Workshop on Reconfigurable Computing, ARC 2006, held in Delft, The Netherlands, in March 2006. The 22 revised full papers and 35 revised short papers presented were thoroughly reviewed and selected from 95 submissions. The papers are organized in topical sections on applications, power, image processing, organization and architecture, networks and communication, security, and tools.