PPT-1 Priority Queues (Heaps)

Sections 61 to 65 2 Priority Queues Regular queue supports First In First Out Enqueue add a new element Dequeue remove oldest element in queue Data structure supports Insert add a new element. Priority queues are fundamental in the design of modern multiprocessor algorithms with many classical applications ranging from numerical algorithms through discrete event simulation and expert systems While highly scalable approaches have been intr Data . Structures. Self-Adjusting. Data . Structures. 2. Lists. [D.D. . Sleator. , R.E. . Tarjan. , . Amortized Efficiency of List Update Rules. , Proc. 16. th. Annual ACM Symposium on Theory of Computing, 488-492, 1984]. COL 106. Shweta Agrawal and . Amit. Kumar. 2. Revisiting FindMin. Application: Find the smallest ( or highest priority) item quickly. Operating system. needs to schedule jobs according to priority instead of FIFO. . Schütze. and Christina . Lioma. Lecture . 20: Crawling. 1. Overview. . R. ecap . . A simple crawler. . A real crawler. 2. Outline. . R. ecap . . A simple crawler. . A real crawler. 3. 4. Search. Lecture 16. CS2110 Spring 2015. Readings and Homework. Read Chapter 26. “A Heap Implementation” to learn about heaps. Exercise: . Salespeople often make matrices that show all the great features of their product that the competitor’s product lacks. Try this for a heap versus a BST. First, try and . Jeff Chase. Duke University. Recap: threads on the metal. An OS implements . synchronization objects . using a combination of elements:. Basic . sleep. /. wakeup. primitives of some form.. Sleep. places the thread TCB on a . A heap is a binary tree.. A heap is best implemented in sequential representation (using an array).. Two important uses of heaps are: . (i) efficient implementation of priority queues. (ii) sorting -- Heapsort.. <number>. Adaptable Priority Queues. 3. a. 5. g. 4. e. © 2014 Goodrich, Tamassia, Goldwasser. Presentation for use with the textbook . Data Structures and Algorithms in Java, 6. th. edition. , by M. T. Goodrich, R. Tamassia, and M. H. Goldwasser, Wiley, 2014. Lecture . 16. CS2110 . Fall 2017. Abstract vs concrete data structures. Abstract data structures are . interfaces. they specify only . interface . (method names and specs). not . implementation. (method bodies, fields, . Prof. . Neary. Based on slides from previous iterations of this course. Today’s Topics. Review of Min Heaps. Introduction of Left-. ist. Heaps. Merge Operation. Heap Operations. Review of Heaps. Min Binary Heap. Lecture . 16. CS2110 . Spring 2018. Announcements. A4 due TOMORROW. Late deadline is Sunday.. A5 released. Due next Thursday. .. Deadline for Prelim 1 regrade requests is tomorrow.. Remember to complete your TA evaluations by . CS232 – Lecture 9. Chapter 9: Priority Queues, Heaps, and Graphs. 9.1 – Priority Queues. 9.2 – Heaps. 9.3 – Introduction to Graphs. 9.4 – Formal Specification of a Graph ADT. 9.5 – Graph Applications. Making queues a first class citizen : Abstracting queues in the UApi Magnus Karlsson & Björn Töpel, Intel Problem Statement 2 bind(af_xdp_fd, netdev, queue_id) Ethtool using queue_id UAPI Drivers decide what queue ids to use for what. No standard Definition of a . d. -ary min heap . Implementation as a complete tree. Examples of binary, ternary, quaternary, and quinary min heaps. Properties. Relative speeds. Optimal choice is a quaternary heap.