Übersicht			Auf mobile öffnen

Lieferstatus:	Auf Bestellung (Lieferzeit unbekannt)
Veröffentlichung:	Juni 2015
Genre:	EDV / Informatik
	Applied mathematics / C / Compilers & interpreters / Compilers and Interpreters / Computer Graphics / computer science / Engineering mathematics / Graphics programming / Mathematical and Computational Engineering / Mathematical and Computational Engineering Applications / Maths for engineers / Programming languages (Electronic computers) / Programming Languages, Compilers, Interpreters mehr...
ISBN:	9783658101121
EAN-Code:	9783658101121
Verlag:	Springer EN
Einband:	Kartoniert
Sprache:	English
Dimensionen:	H 210 mm / B 148 mm / D
Gewicht:	2703 gr
Seiten:	187
Illustration:	XVI, 187 p. 41 illus., 5 illus. in color., farbige Illustrationen, schwarz-weiss Illustrationen
Zus. Info:	EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025.
Bewertung:	Titel bewerten / Meinung schreiben

Inhalt:

Ralf Karrenberg presents Whole-Function Vectorization (WFV), an approach that allows a compiler to automatically create code that exploits data-parallelism using SIMD instructions. Data-parallel applications such as particle simulations, stock option price estimation, or video decoding require the same computations to be performed on huge amounts of data. Without WFV, one processor core executes a single instance of a data-parallel function. WFV transforms the function to execute multiple instances at once using SIMD instructions. The author describes an advanced WFV algorithm that includes a variety of analyses and code generation techniques. He shows that this approach improves the performance of the generated code in a variety of use cases.ContentsIntroduction, Foundations & Terminology, Related WorkSIMD Property AnalysesWhole-Function VectorizationDynamic Code Variants, Evaluation, Conclusion, OutlookTarget GroupsComputer science researchers and students working in data-parallel computingSoftware and compiler engineers in the fields high-performance computing and compiler constructionAbout the AuthorRalf Karrenberg received his PhD in computer science at Saarland University in 2015. His seminal research on compilation techniques for SIMD architectures found wide recognition in both academia and the CPU and GPU industry. Currently, he is working for NVIDIA in Berlin. Prior to that, he contributed to research and development for visual effects in blockbuster movies at Weta Digital, New Zealand.