{"product_id":"approximate-computing-techniques-from-component-to-applicationlevel-9783030947071","title":"Approximate Computing Techniques: From Component- to Application-Level","description":"\u003cp\u003e\u003c\/p\u003e\u003cblockquote\u003e\n\u003cbr\u003eThis book provides a comprehensive overview of Approximate Computing (AxC), a technique for improving performance or reducing power consumption in computing systems, with real-world applications and design and validation techniques. \u003c\/blockquote\u003e\u003cp\u003e\u003cstrong\u003eFormat\u003c\/strong\u003e: Paperback \/ softback\u003cbr\u003e\u003cstrong\u003eLength\u003c\/strong\u003e: 531 pages\u003cbr\u003e\u003cstrong\u003ePublication date\u003c\/strong\u003e: 11 June 2023\u003cbr\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e: Springer Nature Switzerland AG\u003cbr\u003e\u003c\/p\u003e \u003cp\u003e\u003cbr\u003eThis comprehensive book serves as a vital resource for anyone seeking to delve into the cutting-edge field of Approximate Computing (AxC), a groundbreaking technique that holds immense potential for enhancing the performance, cost-effectiveness, and energy efficiency of computing systems. The authors, experts in their respective fields, provide a comprehensive exploration of the various design and validation techniques employed in AxC, as well as their seamless integration into computing systems. They also present a diverse range of real-world AxC applications, spanning from mobile devices to high-performance computing platforms and even safety-critical domains.\u003cbr\u003e\u003cbr\u003eIn the introductory chapter, the authors provide a succinct overview of AxC, highlighting its origins, principles, and applications. They explain how AxC leverages mathematical approximations and statistical techniques to achieve computational efficiency without compromising accuracy. The chapter also sheds light on the challenges and opportunities associated with AxC, such as the need for efficient algorithms, accurate models, and rigorous validation methodologies.\u003cbr\u003e\u003cbr\u003eThe subsequent chapters delve into the intricacies of AxC design and validation. The authors discuss various approaches, including genetic algorithms, neural networks, and machine learning, for designing efficient AxC systems. They also explore techniques for validating the accuracy and reliability of AxC solutions, such as simulation, experimental validation, and performance analysis.\u003cbr\u003e\u003cbr\u003eThe book further explores the integration of AxC into various computing systems. The authors discuss the challenges and opportunities of integrating AxC into existing hardware and software architectures, as well as the impact of AxC on system performance, power consumption, and energy efficiency. They also provide examples of successful AxC implementations in various industries, such as telecommunications, healthcare, and finance.\u003cbr\u003e\u003cbr\u003eIn conclusion, this book serves as a valuable resource for researchers, engineers, and practitioners interested in advancing the state-of-the-art in Approximate Computing. It provides a comprehensive and up-to-date overview of the field, covering the latest research, techniques, and applications. With its practical insights and comprehensive coverage, this book will empower readers to leverage the power of AxC to design and implement efficient and cost-effective computing systems that meet the ever-growing demands of modern computing.\u003cbr\u003eThis comprehensive book serves as a vital resource for anyone seeking to delve into the cutting-edge field of Approximate Computing (AxC), a groundbreaking technique that holds immense potential for enhancing the performance, cost-effectiveness, and energy efficiency of computing systems. The authors, experts in their respective fields, provide a comprehensive exploration of the various design and validation techniques employed in AxC, as well as their seamless integration into computing systems. They also present a diverse range of real-world AxC applications, spanning from mobile devices to high-performance computing platforms and even safety-critical domains.\u003cbr\u003e\u003cbr\u003eIn the introductory chapter, the authors provide a succinct overview of AxC, highlighting its origins. Its origins, principles, and applications. They explain how AxC leverages mathematical approximations and statistical techniques to achieve computational efficiency without compromising accuracy. The chapter also sheds light on the challenges and opportunities associated with AxC, such as the need for efficient algorithms, accurate models, and rigorous validation methodologies.\u003cbr\u003e\u003cbr\u003eThe subsequent chapters delve into the intricacies of AxC design and validation. The authors discuss various approaches, including genetic algorithms, neural networks, and machine learning, for designing efficient AxC systems. They also explore techniques for validating the accuracy and reliability of AxC solutions, such as simulation, experimental validation, and performance analysis.\u003cbr\u003e\u003cbr\u003eThe book further explores the integration of AxC into various computing systems. The authors discuss the challenges and opportunities of integrating AxC into existing hardware and software architectures, as well as the impact of AxC on system performance, power consumption, and energy efficiency. They also provide examples of successful AxC implementations in various industries, such as telecommunications, healthcare, and finance.\u003cbr\u003e\u003cbr\u003eIn conclusion, this book serves as a valuable resource for researchers, engineers, and practitioners interested in advancing the state-of-the-art in Approximate Computing. It provides a comprehensive and up-to-date overview of the field, covering the latest research, techniques, and applications. With its practical insights and comprehensive coverage, this book will empower readers to leverage the power of AxC to design and implement efficient and cost-effective computing systems that meet the ever-growing demands of modern computing.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWeight\u003c\/strong\u003e: 842g\u003cbr\u003e\u003cstrong\u003eDimension\u003c\/strong\u003e: 235 x 155 (mm)\u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9783030947071\u003cbr\u003e \u003cstrong\u003eEdition number\u003c\/strong\u003e: 1st ed. 2022\u003c\/p\u003e","brand":"Shulph Ink","offers":[{"title":"Paperback \/ softback","offer_id":44311987552506,"sku":"9783030947071","price":48.2,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/products\/1688139269837_book.jpg?v=1688292344","url":"https:\/\/shulphink.com\/products\/approximate-computing-techniques-from-component-to-applicationlevel-9783030947071","provider":"Shulph Ink","version":"1.0","type":"link"}