PPT-Reconfigurable MapReduce Framework & Accelerator

Presented By Shefali Gundecha Srinivas Narne Yash Kulkarni Papers to be discussed Y Shan B Wang J Yan Y Wang N Xu and H Yang   FPMR MapReduce Framework on FPGA A Case Study of . Based on the text by Jimmy Lin and Chris Dryer; and on the yahoo tutorial on . mapreduce. at . http://developer.yahoo.com/hadoop/tutorial/index.html. Namenode responsibilities:. Namespace management: file name, locations, access privileges etc.. 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. by . Ahmed . Alawneh. , Mohammed Mansour and . Alaa. . Rawajbeh. . The supervisor: Dr. . Allam. . Mousa.  . . 2014. An-. Najah. National University . Fuculty. of Engineering . Telecommunication Engineering Department . Parallel Computing. MapReduce. Examples. Parallel Efficiency. Assignment. Parallel Computing. Parallel efficiency with . p. processors. Traditional parallel computing:. focus on compute intensive tasks. , the Big Data Workhorse. Vyassa Baratham, Stony Brook University. April 20, 2013, 1:05-2:05pm. cSplash. 2013. Use several computers to process large amounts of data. Often significant . distribution overhead. Presented by : Shreya . sriperumbuduri. . Siddharth. . ambadasu. . Jayalakshmi. . muthiah. 1/57. Citation. El-. Araby. , E.; Gonzalez, I.; El-. Ghazawi. , T., "Virtualizing and sharing reconfigurable resources in High-Performance Reconfigurable Computing systems," High-Performance Reconfigurable Computing Technology and Applications, 2008. HPRCTA 2008. Second International Workshop on , vol., no., pp.1,8, 16-16 Nov. 2008. MapReduce Framework . Michael T. Goodrich. Dept. of Computer Science. MapReduce. A . framework for designing computations for large clusters of computers.. Decouples . location . from data and computation. Chris Morales. Kaz . Onishi. 1. Wireless Sensor Networks. Expected to be :. Autonomous. Low Power. Context aware. Flexible. Can have thousands of nodes spread out. Makes development and support complicated. Hui. Li. Geoffrey Fox. Research Goal. provide . a uniform . MapReduce programming . model that works . on HPC . Clusters or . Virtual Clusters cores . on traditional Intel architecture chip, cores on . Presented by Jinpeng Zhou. CS 2310 Seminar, 12/05/2017. Background. SOA. Service Oriented Architecture. A high-level architecture for distributed systems. Service means programs, databases, processes. ”. 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. Jimmy Lin. The iSchool. University of Maryland. Monday, March 30, 2009. This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 United States. See http://creativecommons.org/licenses/by-nc-sa/3.0/us/ for details. Madhu M Nayak Assistant Professor, Department of C SE, GSSSIETW, Mysuru Pradeep.S Assistant Professor, Department of C SE, GEC, Kushal Nagar Abstract - Due to the increasing popularity of cheap 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.