PPT-Techniques and Structures in Concurrent Programming

Author : pasty-toler | Published Date : 2016-11-14

Wilfredo Velazquez Outline Basics of Concurrency Concepts and Terminology Advantages and Disadvantages Amdahls Law Synchronization Techniques Concurrent Data Structures

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Techniques and Structures in Concurrent Programming: Transcript


Wilfredo Velazquez Outline Basics of Concurrency Concepts and Terminology Advantages and Disadvantages Amdahls Law Synchronization Techniques Concurrent Data Structures Parallel Correctness. Not surprisi ngly peo ple started to think about ways to merge synchronization int o a more structured programming environment One such approach that emerged was the monitor First described by Per Brinch Hansen BH73 and later re64257ned by Tony Hoa In building concurrent FIFO queues this reasoning has led re searchers to propose combiningbased concurrent queues This paper takes a different approach showing how to rely on fetchandadd FA a less powerful primitive that is available on x86 process R. Rivest Editor Electronic Mail, Return Addresses, and Digital Pseudonyms L. Chaum University of California, Berkeley technique based on public key cryptography is presented that allows an electro Pavol. . Cerny. . Vasu. Singh . Thomas . Wies. Part III. – Message Passing Concurrency. The Downsides . of Classical Shared Memory Concurrency. shared memory typically implies . physically. Manolis. . Koubarakis. Data Structures and Programming Techniques. 1. The ADT Queue. A . queue. . Q. of items of type . T. is a sequence of items of type . T. on which the following operations are defined:. Manolis. . Koubarakis. Data Structures and Programming Techniques. 1. The Utility . make. The . make. utility automatically determines which pieces of a large program need to be recompiled, and issues commands to recompile them.. Manolis. . Koubarakis. Data Structures and Programming Techniques. 1. Dynamic Sets. Sets are fundamental for mathematics but also for computer science.. In computer science, we usually study . dynamic sets . Data Structures and Programming Techniques. 1. External Searching. So far we have assumed that our data structures are stored in main memory. However, if the size of a data structure is too big then it will be stored on . . Koubarakis. 1. Data Structures and Programming Techniques. Multi-Way Search Trees. Multi-way trees . are trees such that each internal node can have many children.. Let us assume that the . entries. Manolis. . Koubarakis. Data Structures and Programming Techniques. 1. Weighted Graphs. Weighted graphs . are directed graphs in which numbers called . weights. are attached to the directed edges.. Example. Koubarakis. Data Structures and Programming Techniques. 1. Red-Black Trees. AVL trees and (2,4) trees have very nice properties, but:. AVL trees might need many rotations after a removal. (2,4) trees might require many split or fusion operations after an update. . Synchronization Algorithms . and Concurrent Programming. Gadi Taubenfeld. Chapter 3 . Mutual Exclusion using atomic registers: Advanced Topics. Version: . June 2014. Chapter 3. Synchronization Algorithms and Concurrent Programming Gadi Taubenfeld © 2014. . Synchronization Algorithms . and Concurrent Programming. Gadi Taubenfeld. Chapter 2 . Mutual Exclusion using atomic registers: Basic Topics. Version: . June 2014. Chapter 2. Synchronization Algorithms and Concurrent Programming Gadi Taubenfeld © 2014. . Synchronization Algorithms . and Concurrent Programming. Gadi Taubenfeld. Chapter 7 . Multiple resources. The dinning philosophers problem . Version: . June 2014. Chapter 7. Synchronization Algorithms and Concurrent Programming Gadi Taubenfeld © 2014.

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