PPT-PRAM Algorithms

Sathish Vadhiyar PRAM Model Introduction Parallel Random Access Machine Allows parallelalgorithm designers to treat processing power as unlimited Ignores complexity of interprocess communication. Rahul. . Santhanam. University of Edinburgh. Plan of the Talk. Preliminaries and Motivation. Informational Bottlenecks: Proof Complexity and Related Models. Computational Bottlenecks: OPP and Compression. Some of the fastest known algorithms for certain tasks rely on chance. Stochastic/Randomized Algorithms. Two common variations. Monte Carlo. Las Vegas. We have already encountered some of both in this class. Lecture 6. The maximum contiguous subsequence sum problem.. 8/25/2009. 1. ALG0183 Algorithms & Data Structures by Dr Andy Brooks. Weiss Chapter 5.3. There are many algorithms to solve this problem and their performances vary dramatically.. 1. Graph Algorithms. Many problems are naturally represented as graphs. Networks, Maps, Possible paths, Resource Flow, etc.. Ch. 3 focuses on algorithms to find connectivity in graphs. Ch. 4 focuses on algorithms to find paths within graphs. vs. Sequential Algorithms. Design of efficient algorithms. A parallel computer is of little use unless efficient parallel algorithms are available.. The issue in designing parallel algorithms are very different from those in designing their sequential counterparts.. George Caragea, and Uzi Vishkin. University of Maryland. 1. Speaker. James Edwards. It has proven to be quite . difficult. to obtain significant performance improvements using current parallel computing platforms.. Annie . Yang and Martin Burtscher*. Department of Computer Science. Highlights. MPC compression algorithm. Brand-new . lossless . compression algorithm for single- and double-precision floating-point data. Time for Hardware Upgrade. Uzi Vishkin. . . The pompous version. After 40 years of “wandering in the desert”, general-purpose parallelism is very close to capturing the “promised land” of mainstream computing. Reinvention of Computing for Parallelism. Uzi Vishkin. . Same title, . http://www.umiacs.umd.edu/users/vishkin/XMT/. cacm2010.pdf. , to appear in CACM. Conclusion of Intro Slide(s). Productivity: code development time + runtime . matter and can matter more: . Big . lead of PRAM algorithms on prototype-HW. Uzi Vishkin. There is nothing more practical than a good theory. -- James C. Maxwell. Mainstream many-cores are in trouble. Raman Veerappan. EPS 109 Final Project. Introduction. Goals. To examine various maze solving algorithms using MATLAB determine which algorithms are most effective for which mazes. Two main algorithms examined. Computing. Jie Liu. , . Ph.D.. Professor. Computer Science Division. Western Oregon University. Monmouth, Oregon, USA. liuj@wou.edu. outline. The . fastest computers. The PRAM model. The O(1) algorithm that finds the max. Sathish. . Vadhiyar. PRAM Model - Introduction. Parallel Random Access Machine. Allows parallel-algorithm designers to treat processing power as unlimited. Ignores complexity of inter-process communication. Problem - a well defined task.. Sort a list of numbers.. Find a particular item in a list.. Find a winning chess move.. Algorithms. A series of precise steps, known to stop eventually, that solve a problem..