PPT-CSE332: Data Abstractions

Lecture 19 Analysis of ForkJoin Parallel Programs Dan Grossman Spring 2010 Where are we Done How to use fork and join to write a parallel algorithm Why using divideandconquer with lots of small tasks is best. All Programmable Abstractions push beyond traditional RTL design methodologies to automate all aspects of system development and algorithm deployment into all programmable FPGAs SoC and 3D ICs Xilinx and its Alliance members are working together to 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 5: Binary Heaps, Continued. Tyler Robison. Summer 2010. 1. Review. 2. Priority Queue ADT: . insert. comparable object, . deleteMin. Binary heap data structure: Complete binary tree where each node has a lesser priority than its parent (greater value). for . SoC. . Verification. Pramod Subramanyan. , . Yakir. . Vizel. , . Sayak. Ray and Sharad . Malik. FMCAD . 2015. On-chip Interconnect. CPU. GPU. Camera. Touch. Flash. DMA. WiFi. /3G. GPS. …. MMU+. String . Verification. Given a string manipulating program, . string . analysis . determines . all possible values . that a string expression can take during any program execution. Using string analysis we . Watercolor Paint - Abstractions. Watercolor Paint – Non-Representational. Pastel Abstractions. 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. 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. Disjoint Set Union-Find . and . Minimum Spanning Trees. Kate Deibel. Summer 2012. August 13, 2012. CSE 332 Data Abstractions, Summer 2012. 1. Making Connections. You have a set of nodes (numbered 1-9) on a network. . 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 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. 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. 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.