PPT-Finding Optimal Program Abstractions
Author : jane-oiler | Published Date : 2015-11-20
Mayur Naik Georgia Tech Xin Zhang Georgia Tech Hongseok Yang Oxford Percy Liang Stanford Mooly Sagiv TelAviv U J oint work with Static Analysis 70s to
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Finding Optimal Program Abstractions: Transcript
Mayur Naik Georgia Tech Xin Zhang Georgia Tech Hongseok Yang Oxford Percy Liang Stanford Mooly Sagiv TelAviv U J oint work with Static Analysis 70s to 90s. Bi kh Bh tt ac arya Professor Department of Mechanical Engineering IIT Kanpur Joint Initiative of IITs and IISc Funded by MHRD brPage 2br NPTEL Mechanical Engineering Modeling and Control of Dynamic electroMechanical System Module 4 Lecture 33 Jo Introduction Softwarede64257ned networking SDN has received a lot of attention in recent years as a means of addressing some of the longstanding challenges in networking SDN starts from two simple ideas i generalize network hardware so it provide Dictionary ADT. : Arrays, Lists and . Trees. Kate Deibel. Summer 2012. June 27, 2012. CSE 332 Data Abstractions, Summer 2012. 1. Where We Are. Studying the absolutely essential ADTs of computer science and classic data structures for implementing them. Watercolor Paint - Abstractions. Watercolor Paint – Non-Representational. Pastel Abstractions. 6/16/2010. Parallel Programming Abstractions. 1. Tasks . vs. Threads. Similar but not the same.. 6/16/2010. Parallel Programming Abstractions. 2. h/w processors. Operating System. T. hreads. Task Scheduler. Lecture . 27. : . A Few Words on NP. Dan Grossman. Spring 2010. This does not belong in CSE332. This lecture mentions some highlights of . NP. , the . P. vs. . NP. question, and . NP. -completeness. Cynthia Lee. CS106X. Today’s Topics. Quick final exam discussion. Details/logistics, topics, sources for practice problems. Quarter wrap-up. Putting it all together: what have we accomplished together this quarter?. Keith Dalbey, Ph.D.. Sandia National Labs, Dept 1441, Optimization and Uncertainty Quantification. Michael Levy, Ph.D.. Sandia National Labs, Dept 1442, Numerical Analysis and Applications. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy’s National Nuclear Security Administration under Contract DE-AC04-94AL85000.. Chapter 1 — Computer Abstractions and Technology — . 2. Classes of Computers. Personal computers. General purpose, variety of software. Subject to cost/performance tradeoff. Server computers. Network based. Graphs and Graph Traversals. Kate Deibel. Summer 2012. July 25, 2012. CSE 332 Data Abstractions, Summer 2012. 1. Last Time. We introduced the idea of graphs and their associated terminology. Key terms included:. Lecture 19: Analysis of Fork-Join Parallel Programs. Dan Grossman. Spring 2010. Where are we. Done:. How to use . fork. , and . join. to write a parallel algorithm. Why using divide-and-conquer with lots of small tasks is best. Lecture 6: Dictionaries; Binary Search Trees. Dan Grossman. Spring 2010. Where we are. Studying the absolutely essential ADTs of computer science and classic data structures for implementing them. ADTs so far:. Lecture 9: B Trees. Dan Grossman. Spring 2010. Our goal. Problem: A dictionary with so much data most of it is on disk. Desire: A balanced tree (logarithmic height) that is even shallower than AVL trees so that we can minimize disk accesses and exploit disk-block size. Lecture 5: Binary Heaps, Continued. Dan Grossman. Spring 2010. Review. Priority Queue ADT: . insert. comparable object, . deleteMin. Binary heap data structure: Complete binary tree where each node has priority value greater than its parent.
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