Proceedings of the 2012 ACM SIGPLAN X10 Workshop PDF Download
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Author: Association for Computing Machinery
Publisher:
ISBN:
Category : Computer science
Languages : en
Pages : 46
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Book Description
Author: Association for Computing Machinery
Publisher:
ISBN:
Category : Computer science
Languages : en
Pages : 46
Get Book Here
Book Description
Author:
Publisher:
ISBN:
Category : Computer science
Languages : en
Pages : 46
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Book Description
Author:
Publisher:
ISBN:
Category : Object-oriented programming (Computer science)
Languages : en
Pages : 64
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Book Description
Author: Association for Computing Machinery
Publisher:
ISBN:
Category : Computer science
Languages : en
Pages : 47
Get Book Here
Book Description
Author: Association for Computing Machinery
Publisher:
ISBN:
Category : Object-oriented programming (Computer science)
Languages : en
Pages : 64
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Book Description
Author:
Publisher:
ISBN:
Category : Computer science
Languages : en
Pages : 47
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Book Description
Author: Claudia Fohry
Publisher:
ISBN: 9781450343862
Category : Computer science
Languages : en
Pages :
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Book Description
PLDI '16: ACM SIGPLAN Conference on Programming Language Design and Implementation Jun 13, 2016-Jun 17, 2016 Santa Barbara, USA. You can view more information about this proceeding and all of ACM�s other published conference proceedings from the ACM Digital Library: http://www.acm.org/dl.
Author: Olivier Tardieu
Publisher:
ISBN: 9781450335867
Category : Computer science
Languages : en
Pages : 38
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Book Description
Author: Sascha Roloff
Publisher: Springer
ISBN: 9811383871
Category : Technology & Engineering
Languages : en
Pages : 168
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Book Description
This book covers two main topics: First, novel fast and flexible simulation techniques for modern heterogeneous NoC-based multi-core architectures. These are implemented in the full-system simulator called InvadeSIM and designed to study the dynamic behavior of hundreds of parallel application programs running on such architectures while competing for resources. Second, a novel actor-oriented programming library called ActorX10, which allows to formally model parallel streaming applications by actor graphs and to analyze predictable execution behavior as part of so-called hybrid mapping approaches, which are used to guarantee real-time requirements of such applications at design time independent from dynamic workloads by a combination of static analysis and dynamic embedding.
Author: Matthias Dehmer
Publisher: CRC Press
ISBN: 1315353598
Category : Computers
Languages : en
Pages : 290
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Book Description
Big Data of Complex Networks presents and explains the methods from the study of big data that can be used in analysing massive structural data sets, including both very large networks and sets of graphs. As well as applying statistical analysis techniques like sampling and bootstrapping in an interdisciplinary manner to produce novel techniques for analyzing massive amounts of data, this book also explores the possibilities offered by the special aspects such as computer memory in investigating large sets of complex networks. Intended for computer scientists, statisticians and mathematicians interested in the big data and networks, Big Data of Complex Networks is also a valuable tool for researchers in the fields of visualization, data analysis, computer vision and bioinformatics. Key features: Provides a complete discussion of both the hardware and software used to organize big data Describes a wide range of useful applications for managing big data and resultant data sets Maintains a firm focus on massive data and large networks Unveils innovative techniques to help readers handle big data Matthias Dehmer received his PhD in computer science from the Darmstadt University of Technology, Germany. Currently, he is Professor at UMIT – The Health and Life Sciences University, Austria, and the Universität der Bundeswehr München. His research interests are in graph theory, data science, complex networks, complexity, statistics and information theory. Frank Emmert-Streib received his PhD in theoretical physics from the University of Bremen, and is currently Associate professor at Tampere University of Technology, Finland. His research interests are in the field of computational biology, machine learning and network medicine. Stefan Pickl holds a PhD in mathematics from the Darmstadt University of Technology, and is currently a Professor at Bundeswehr Universität München. His research interests are in operations research, systems biology, graph theory and discrete optimization. Andreas Holzinger received his PhD in cognitive science from Graz University and his habilitation (second PhD) in computer science from Graz University of Technology. He is head of the Holzinger Group HCI-KDD at the Medical University Graz and Visiting Professor for Machine Learning in Health Informatics Vienna University of Technology.
