PPT-CSE332: Data Abstractions

Lecture 7 AVL Trees Tyler Robison Summer 2010 1 The AVL Tree Data Structure An AVL tree is a BST In addition Balance property balance of every node is between 1 and 1 balance node. 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 Chris Rossbach, Microsoft Research. Jon Currey, Microsoft Research. Emmett . Witchel. , University of Texas at Austin. HotOS. 2011. Lots of GPUs. Must they be so hard to use?. We need dataflow…. GPU Haiku . Matei Zaharia, . Benjamin . Hindman. , Andy . Konwinski. , Ali . Ghodsi. , Anthony Joseph, Randy Katz, Scott . Shenker. , Ion . Stoica. Background. Clusters of commodity servers . have become a . major computing . Lecture 6: Programming languages. USABILITY OF NOTATIONS. Cognitive Dimensions of Notations. ‘Discussion tools’ for use when considering alternative designs of programming languages, and other complex information systems. Lecture 21: Amortized Analysis. Dan Grossman. Spring 2010. Amortized . Recall our plain-old stack implemented as an array that doubles its size if it runs out of room. How can we claim . push. is . O. 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. 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:. CSE 332 Data Abstractions: A Heterozygous Forest of AVL, Splay, and B Trees Kate Deibel Summer 2012 July 2, 2012 CSE 332 Data Abstractions, Summer 2012 1 From last time… Binary search trees can give us great performance due to providing a structured binary search. 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 15: Introduction to Graphs. Dan Grossman. Spring 2010. Graphs. A graph is a formalism for representing relationships among items. Very general definition because very general concept. A . graph. 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. Lecture . 13: . Introduction to Graphs. Dan Grossman. Fall 2013. Graphs. A graph is a formalism for representing relationships among items. Very general definition because very general concept. A . graph.