PPT-Dataflow Analysis for Software Product Lines

Author : lastinsetp | Published Date : 2020-08-06

Claus Brabrand IT University of Copenhagen Universidade Federal de Pernambuco brabranditudk Márcio Ribeiro Universidade Federal de Alagoas Universidade Federal

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Dataflow Analysis for Software Product Lines: Transcript


Claus Brabrand IT University of Copenhagen Universidade Federal de Pernambuco brabranditudk Márcio Ribeiro Universidade Federal de Alagoas Universidade Federal de Pernambuco mmr3cinufpebr . Dependable rights trademark & brand licensing software solutions system. Web based brand licensing, royalty & approval systems to licensors, agents & licensees. (and the Naiad system). Frank McSherry. , Derek G. Murray,. Rebecca Isaacs, . Michael Isard. Microsoft Research, Silicon Valley. Data-parallel dataflow. 1. 2. 3. 4. 5. 1. 4. 2. 3. 6. 6. 5. A. B. C. D. via Dataflow Flattening. Bertrand Anckaert. Ghent University/. Boston . Consulting Group. The Third International Conference on Emerging Security. Information, Systems and Technologies. . SECURWARE 2009. Yuan Lin. 1. , Yoonseo Choi. 1. , Scott Mahlke. 1. , Trevor Mudge. 1. , . Chaitali. Chakrabarti. 2. 1. Advanced Computer Architecture Lab, University of Michigan at Ann Arbor. 2. Department of Electrical Engineering, Arizona State University. Building Relational Web-Applications. Avraham . Leff. James T. . Rayfield. IBM T.J. Watson Research Center. {. avraham,jtray. }@us.ibm.com. OOPSLA’07. Presented by David Gonzalez. Key Insights:. Derek G. Murray. Michael Isard. Frank McSherry. Paul Barham. Rebecca Isaacs. Martín Abadi. Microsoft Research. 1. Batch processing. Stream processing. Graph processing. Timely dataflow. In. ⋈. #x. Frank McSherry. , Derek G. Murray,. Rebecca Isaacs, Michael Isard. Microsoft Research, Silicon Valley. Data-parallel dataflow. 1. 2. 3. 4. 5. 1. 4. 2. 3. 6. 6. 5. A. B. C. D. E. k1:. k2:. k3:. Data-parallel dataflow. Dr. Kathryn Anne Weiss. FSW Core Cognizant Engineer. December 11, 2013. JPL FSW Product Line. Product Line Motivation and Objectives. What . is the JPL Flight Software Product Line?. Product Line Development and Evolution. Finding Optimum Abstractions in Parametric Dataflow Analysis Xin Zhang Georgia Tech Mayur Naik Georgia Tech Hongseok Yang University of Oxford A Key Challenge for Static Analysis Precision Scalability Organizational. . Structure. . and. Productization. Lecture 17. Sjaak. . Brinkkemper. Garm. . Lucassen. 1 . Juni. 2017. Outline. Organizational. . growth. . and. . structures. Positioning the product manager. To perform optimizations like constant propagation or dead code elimination, we must. Analyze program to find opportunities for performing optimizations safely. Transform program. Analysis is called . Shail Dave. 1. , . Youngbin. Kim. 2. , . Sasikanth. Avancha. 3,. Kyoungwoo. Lee. 2. , Aviral Shrivastava. 1. [1] Compiler Microarchitecture Lab, Arizona State University. [2] Department of Computer Science, Yonsei University. SCNN: An Accelerator for Compressed-sparse Convolutional Neural Networks. 9 authors @ NVIDIA, MIT, Berkeley, Stanford. ISCA . 2017. Convolution operation. Reuse. Memory: size vs. access energy. Dataflow decides reuse. Software Architecture Course. Pre-Masters Studies. Computer Science Department. Cairo University. Software Product Line. Introduction. What is Software Product Line. Software Product Line Concepts. Binding Times.

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