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Outlines modern research directions for pre-silicon power modeling and post-silicon power characterization. An invaluable reference for anyone with an interest in power consumption and how it affects the performance of future computing systems.
Outlines modern research directions for pre-silicon power modeling and post-silicon power characterization. An invaluable reference for anyone with an interest in power consumption and how it affects the performance of future computing systems.
This book describes for readers a methodology for dynamic power estimation, using Transaction Level Modeling (TLM). The methodology exploits the existing tools for RTL simulation, design synthesis and SystemC prototyping to provide fast and accurate power estimation using Transaction Level Power Modeling (TLPM). Readers will benefit from this innovative way of evaluating power on a high level of abstraction, at an early stage of the product life cycle, decreasing the number of the expensive design iterations.
The six volumes LNCS 11619-11624 constitute the refereed proceedings of the 19th International Conference on Computational Science and Its Applications, ICCSA 2019, held in Saint Petersburg, Russia, in July 2019. The 64 full papers, 10 short papers and 259 workshop papers presented were carefully reviewed and selected form numerous submissions. The 64 full papers are organized in the following five general tracks: computational methods, algorithms and scientific applications; high performance computing and networks; geometric modeling, graphics and visualization; advanced and emerging applications; and information systems and technologies. The 259 workshop papers were presented at 33 workshops in various areas of computational sciences, ranging from computational science technologies to specific areas of computational sciences, such as software engineering, security, artificial intelligence and blockchain technologies.
Predictive Modeling for Energy Management and Power Systems Engineering introduces readers to the cutting-edge use of big data and large computational infrastructures in energy demand estimation and power management systems. The book supports engineers and scientists who seek to become familiar with advanced optimization techniques for power systems designs, optimization techniques and algorithms for consumer power management, and potential applications of machine learning and artificial intelligence in this field. The book provides modeling theory in an easy-to-read format, verified with on-site models and case studies for specific geographic regions and complex consumer markets. - Presents advanced optimization techniques to improve existing energy demand system - Provides data-analytic models and their practical relevance in proven case studies - Explores novel developments in machine-learning and artificial intelligence applied in energy management - Provides modeling theory in an easy-to-read format
Nano-scale materials have unique electronic, optical, and chemical properties that make them attractive for a new generation of devices. In the second edition of Modeling, Characterization, and Production of Nanomaterials: Electronics, Photonics, and Energy Applications, leading experts review the latest advances in research in the understanding, prediction, and methods of production of current and emerging nanomaterials for key applications. The chapters in the first half of the book cover applications of different modeling techniques, such as Green's function-based multiscale modeling and density functional theory, to simulate nanomaterials and their structures, properties, and devices. The chapters in the second half describe the characterization of nanomaterials using advanced material characterization techniques, such as high-resolution electron microscopy, near-field scanning microwave microscopy, confocal micro-Raman spectroscopy, thermal analysis of nanoparticles, and applications of nanomaterials in areas such as electronics, solar energy, catalysis, and sensing. The second edition includes emerging relevant nanomaterials, applications, and updated modeling and characterization techniques and new understanding of nanomaterials. - Covers the close connection between modeling and experimental methods for studying a wide range of nanomaterials and nanostructures - Focuses on practical applications and industry needs through a solid outlining of the theoretical background - Includes emerging nanomaterials and their applications in spintronics and sensing