PPT-CSE332: Data Abstractions

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 diskblock size. 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 . 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. Watercolor Paint - Abstractions. Watercolor Paint – Non-Representational. Pastel Abstractions. Eurocrypt. May 1. st. , 2017. Rafael Pass, Elaine Shi, . Florian Tramèr. Trusted hardware: . Different . communities. , different . world views. Crypto. Architecture. Systems. & . Security. “Minimal” trusted . 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. 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. 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. 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?. 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 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 . 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.