This book contains extended and revised versions of the best papers presented at the 23rd IFIP WG 10.5/IEEE International Conference on Very Large Scale Integration, VLSI-SoC 2015, held in Daejeon, Korea, in October 2015. The 10 papers included in the book were carefully reviewed and selected from the 44 full papers presented at the conference. The papers cover a wide range of topics in VLSI technology and advanced research. They address the current trend toward increasing chip integration and technology process advancements bringing about new challenges both at the physical and system-design levels, as well as in the test of these systems.
This book contains extended and revised versions of the best papers presented at the 25th IFIP WG 10.5/IEEE International Conference on Very Large Scale Integration, VLSI-SoC 2017, held in Abu Dhabi, United Arab Emirates, in August 2017. The 11 papers included in this book were carefully reviewed and selected from the 33 full papers presented at the conference. The papers cover a wide range of topics in VLSI technology and advanced research. They address the latest scientific and industrial results and developments as well as future trends in the field of System-on-Chip (SoC) Design. On the occasion of the silver jubilee of the VLSI-SoC conference series the book also includes a special chapter that presents the history of the VLSI-SoC series of conferences and its relation with VLSI-SoC evolution since the early 80s up to the present.
The book is a comprehensive guide that explores the use of artificial intelligence and machine learning in drug discovery and development covering a range of topics, including the use of molecular modeling, docking, identifying targets, selecting compounds, and optimizing drugs. The intersection of Artificial Intelligence (AI) and Machine Learning (ML) within the field of drug design and development represents a pivotal moment in the history of healthcare and pharmaceuticals. The remarkable synergy between cutting-edge technology and the life sciences has ushered in a new era of possibilities, offering unprecedented opportunities, formidable challenges, and a tantalizing glimpse into the future of medicine. AI can be applied to all the key areas of the pharmaceutical industry, such as drug discovery and development, drug repurposing, and improving productivity within a short period. Contemporary methods have shown promising results in facilitating the discovery of drugs to target different diseases. Moreover, AI helps in predicting the efficacy and safety of molecules and gives researchers a much broader chemical pallet for the selection of the best molecules for drug testing and delivery. In this context, drug repurposing is another important topic where AI can have a substantial impact. With the vast amount of clinical and pharmaceutical data available to date, AI algorithms find suitable drugs that can be repurposed for alternative use in medicine. This book is a comprehensive exploration of this dynamic and rapidly evolving field. In an era where precision and efficiency are paramount in drug discovery, AI and ML have emerged as transformative tools, reshaping the way we identify, design, and develop pharmaceuticals. This book is a testament to the profound impact these technologies have had and will continue to have on the pharmaceutical industry, healthcare, and ultimately, patient well-being. The editors of this volume have assembled a distinguished group of experts, researchers, and thought leaders from both the AI, ML, and pharmaceutical domains. Their collective knowledge and insights illuminate the multifaceted landscape of AI and ML in drug design and development, offering a roadmap for navigating its complexities and harnessing its potential. In each section, readers will find a rich tapestry of knowledge, case studies, and expert opinions, providing a 360-degree view of AI and ML’s role in drug design and development. Whether you are a researcher, scientist, industry professional, policymaker, or simply curious about the future of medicine, this book offers 19 state-of-the-art chapters providing valuable insights and a compass to navigate the exciting journey ahead. Audience The book is a valuable resource for a wide range of professionals in the pharmaceutical and allied industries including researchers, scientists, engineers, and laboratory workers in the field of drug discovery and development, who want to learn about the latest techniques in machine learning and AI, as well as information technology professionals who are interested in the application of machine learning and artificial intelligence in drug development.
This book provides readers with insight into an alternative approach for enhancing the reliability, security, and low power features of integrated circuit designs, related to transient faults, hardware Trojans, and power consumption. The authors explain how the addition of integrated sensors enables the detection of ionizing particles and how this information can be processed at a high layer. The discussion also includes a variety of applications, such as the detection of hardware Trojans and fault attacks, and how sensors can operate to provide different body bias levels and reduce power costs. Readers can benefit from these sensors-based approaches through designs with fast response time, non-intrusive integration on gate-level and reasonable design costs.
The 11 th IFIP International Conference on Very Large Scale Integration, in Montpellier, France, December 3-5,2001, was a great success. The main focus was about IP Cores, Circuits and System Designs & Applications as well as SOC Design Methods and CAD. This book contains the best papers (39 among 70) that have been presented during the conference. Those papers deal with all aspects of importance for the design of the current and future integrated systems. System on Chip (SOC) design is today a big challenge for designers, as a SOC may contain very different blocks, such as microcontrollers, DSPs, memories including embedded DRAM, analog, FPGA, RF front-ends for wireless communications and integrated sensors. The complete design of such chips, in very deep submicron technologies down to 0.13 mm, with several hundreds of millions of transistors, supplied at less than 1 Volt, is a very challenging task if design, verification, debug and industrial test are considered. The microelectronic revolution is fascinating; 55 years ago, in late 1947, the transistor was invented, and everybody knows that it was by William Shockley, John Bardeen and Walter H. Brattein, Bell Telephone Laboratories, which received the Nobel Prize in Physics in 1956. Probably, everybody thinks that it was recognized immediately as a major invention.
This book contains extended and revised versions of the best papers presented at the 24th IFIP WG 10.5/IEEE International Conference on Very Large Scale Integration, VLSI-SoC 2016, held in Tallinn, Estonia, in September 2016. The 11 papers included in the book were carefully reviewed and selected from the 36 full papers presented at the conference. The papers cover a wide range of topics in VLSI technology and advanced research. They address the latest scientific and industrial results and developments as well as future trends in the field of System-on-Chip (SoC) Design.
This book provides comprehensive coverage of Network-on-Chip (NoC) security vulnerabilities and state-of-the-art countermeasures, with contributions from System-on-Chip (SoC) designers, academic researchers and hardware security experts. Readers will gain a clear understanding of the existing security solutions for on-chip communication architectures and how they can be utilized effectively to design secure and trustworthy systems.
This book contains extended and revised versions of the best papers presented at the 26th IFIP WG 10.5/IEEE International Conference on Very Large Scale Integration, VLSI-SoC 2018, held in Verona, Italy, in October 2018. The 13 full papers included in this volume were carefully reviewed and selected from the 27 papers (out of 106 submissions) presented at the conference. The papers discuss the latest academic and industrial results and developments as well as future trends in the field of System-on-Chip (SoC) design, considering the challenges of nano-scale, state-of-the-art and emerging manufacturing technologies. In particular they address cutting-edge research fields like heterogeneous, neuromorphic and brain-inspired, biologically-inspired, approximate computing systems.
This book contains extended and revised versions of the best papers presented at the 27th IFIP WG 10.5/IEEE International Conference on Very Large Scale Integration, VLSI-SoC 2019, held in Cusco, Peru, in October 2019. The 15 full papers included in this volume were carefully reviewed and selected from the 28 papers (out of 82 submissions) presented at the conference. The papers discuss the latest academic and industrial results and developments as well as future trends in the field of System-on-Chip (SoC) design, considering the challenges of nano-scale, state-of-the-art and emerging manufacturing technologies. In particular they address cutting-edge research fields like heterogeneous, neuromorphic and brain-inspired, biologically-inspired, approximate computing systems.
This book pioneers the field of gain-cell embedded DRAM (GC-eDRAM) design for low-power VLSI systems-on-chip (SoCs). Novel GC-eDRAMs are specifically designed and optimized for a range of low-power VLSI SoCs, ranging from ultra-low power to power-aware high-performance applications. After a detailed review of prior-art GC-eDRAMs, an analytical retention time distribution model is introduced and validated by silicon measurements, which is key for low-power GC-eDRAM design. The book then investigates supply voltage scaling and near-threshold voltage (NTV) operation of a conventional gain cell (GC), before presenting novel GC circuit and assist techniques for NTV operation, including a 3-transistor full transmission-gate write port, reverse body biasing (RBB), and a replica technique for optimum refresh timing. Next, conventional GC bitcells are evaluated under aggressive technology and voltage scaling (down to the subthreshold domain), before novel bitcells for aggressively scaled CMOS nodes and soft-error tolerance as presented, including a 4-transistor GC with partial internal feedback and a 4-transistor GC with built-in redundancy.
