PPT-Accelerated Path-Based Timing Analysis with MapReduce

Author : kittie-lecroy | Published Date : 2018-09-29

Tsung Wei Huang and Martin D F Wong Department of Electrical and Computer Engineering ECE University of Illinois at UrbanaChampaign UIUC IL USA 2015 ACM International

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Accelerated Path-Based Timing Analysis with MapReduce: Transcript

Tsung Wei Huang and Martin D F Wong Department of Electrical and Computer Engineering ECE University of Illinois at UrbanaChampaign UIUC IL USA 2015 ACM International Symposium on Physical Design ISPD. & Senior Permission. Michael Edwards. Coordinator of Graduate Admissions. Getting a Head Start. Why encourage students to pursue the Accelerated Option?. Why encourage students to pursue Senior Permission?. Tsung. -Wei Huang. and Martin D. F. Wong. Department of Electrical and Computer Engineering (ECE). University of Illinois at Urbana-Champaign (UIUC), IL, USA. 2015 ACM International Symposium on Physical Design (ISPD). and . Hadoop. Debapriyo Majumdar. Data Mining – Fall 2014. Indian Statistical Institute Kolkata. November 10, 2014. Let’s keep the intro short. Modern data mining: process immense amount of data quickly. , Collective Communication, and Services. Oral Exam, . Bingjing. Zhang. Outline. MapReduce. MapReduce. Frameworks. Iterative . MapReduce. Frameworks. Frameworks Based on . MapReduce. and Alternatives. Parallel Computing. MapReduce. Examples. Parallel Efficiency. Assignment. Parallel Computing. Parallel efficiency with . p. processors. Traditional parallel computing:. focus on compute intensive tasks. Accelerated Reading. Accelerated Reader . combines two key elements of baseline assessment and personalised reading practice to promote reading for pleasure and encourage pupils to use reading to learn.. Why?. In order for year 11 pupils to access their GCSE exams effectively to achieve pupils need to have an average reading age of at least 15 years. 25% of year 11 pupils in the UK have a reading age less than 11 years old.. Objectives. After completing this module you will be able to…. Apply global timing constraints to a simple synchronous design. Use the Xilinx Constraints Editor to specify global timing constraints. Yasin N. Silva and Jason Reed. Arizona State University. 1. This work is licensed under a Creative Commons Attribution-. NonCommercial. -. ShareAlike. 4.0 International License. See http://creativecommons.org/licenses/by-nc-sa/4.0/ for details.. ITEC 7445: EMERGING TECHNOLOGY. NOVEMBER 12, 2012. Accelerated Math. Provided by Renaissance Learning.. A software tool that is used to customize assignments and monitor progress in mathematics.. Creates individualized goals and assignments.. Karen Taylor & . Evangelia. . Antonakos. Bronx Community College. Dept. of Math & Computer Science. Innovative Practices in Developmental Mathematics. LaGCC. , CUNY. April 15, 2016. . Supported by a CUNY course redesign grant awarded to Karen Taylor & Suzanne . ”. Cathy O’Neil & Rachel . Schutt. , 2013. R & Hadoop. Compute squares. 2. R. # create a list of 10 integers. ints. <- 1:10. # equivalent to . ints. <- c(1,2,3,4,5,6,7,8,9,10). # compute the squares. Source. MapReduce. : Simplified Data Processing in Large Clusters. . Jefferey. Dean and Sanjay . Ghemawat. . OSDI 2004. Example Scenario. 3. Genome data from roughly . one million users. 125 MB of data per user. MapReduce. Architecture. MapReduce. Internals. MapReduce. Examples. JobTracker. Interface. MapReduce. : A Real World Analogy. Coins Deposit. ?. MapReduce. : A Real World Analogy. Coins Deposit. Coins Counting Machine.

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