'Sequential algorithm' presentation slideshows

Dense Matrix Algorithms

Dense Matrix Algorithms. Carl Tropper Department of Computer Science McGill University. Dense. Few non-zero entries Topics Matrix-Vector Multiplication Matrix-Matrix Multiplication Solving a System of Linear Equations . Introductory ramblings.

1.13k views • 58 slides

Parallel Computers

Chapter 1. Parallel Computers. Demand for Computational Speed. Continual demand for greater computational speed from a computer system than is currently possible Areas requiring great computational speed include numerical modeling and simulation of scientific and engineering problems.

628 views • 51 slides

Chapter 4, CLR Textbook

Chapter 4, CLR Textbook. Algorithms on Rings of Processors. Algorithms on Rings of Processors. When using message passing, it is common to abstract away from the physical network and to choose a convenient logical network instead.

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Chapter 2: Algorithm Discovery and Design

Chapter 2: Algorithm Discovery and Design. Invitation to Computer Science, Java Version, Third Edition. Objectives. In this chapter, you will learn about Representing algorithms Examples of algorithmic problem solving. Introduction.

762 views • 42 slides

SCALABILITY ANALYSIS

SCALABILITY ANALYSIS. PERFORMANCE AND SCALABILITY OF PARALLEL SYSTEMS. Evaluation Sequential: runtime (Execution time) Ts =T (InputSize) Parallel: runtime (Start-->Last PE ends) Tp =T (InputSize,p,architecture) Note: Cannot be Evaluated in Isolation from the Parallel architecture

549 views • 40 slides

Parallel Event Driven Simulation using GPU (CUDA)

537 views • 38 slides

GAUSSIAN ELIMINATION

GAUSSIAN ELIMINATION. Pham Thi Minh Thu - 20136124. OUTLINE. Sequential Algorithm Parallel Algorithm Row-oriented Algorithm Column-oriented Algorithm Comparison Pipelined, Row-oriented. Gaussian Elimination. Used to solve Ax = b when A is dense

597 views • 33 slides

Computational Modeling and Simulation of Spatiotemporal Characteristics of Crime in Urban Environments

369 views • 32 slides

Multilevel Parallelization Architecture of Boundary Element Solver Engines for Cloud Computing Dipanjan Gope, Don MacM

Multilevel Parallelization Architecture of Boundary Element Solver Engines for Cloud Computing Dipanjan Gope, Don MacMillen, Devan Williams, Xiren Wang. Outline. The need for parallelization Challenges towards effective parallelization

464 views • 29 slides

Chapter 5

490 views • 28 slides

Parallel Implementation of Ant Colony Optimization on Traveling Salesman problem

Parallel Implementation of Ant Colony Optimization on Traveling Salesman problem. Under the supervision of Dr.K.P.Singh. Yogesh sharma IIT2009175 Ankur mangal IIT2009176. Traveling Salesman Problem (TSP).

534 views • 26 slides

Uncompressing a Projection Index with CUDA

304 views • 20 slides

Keshav Pingali Department of Computer Science University of Texas, Austin

The Hunt for Right Abstractions. Keshav Pingali Department of Computer Science University of Texas, Austin. Overview. Abstraction means different things in different areas mathematics/sciences: ignoring some properties of an object so as to focus on the important ones

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Analytical Modeling of Parallel Programs

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Divide and Conquer

Divide and Conquer. Yan Gu. What is Divide and Conquer?. An effective approach to designing fast algorithms in sequential computation is the method known as divide and conquer . Stratege ---- Divide:

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List Ranking on GPUs

369 views • 18 slides

Parallel Algorithms

Parallel Algorithms. several operations can be executed at the same time many problems are most naturally modeled with parallelism A Simple Model for Parallel Processing Approaches to the design of parallel algorithms Speedup and Efficiency of parallel algorithms A class of problems NC

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A SEQUENTIAL IMPORTANCE SAMPLING ALGORITHM FOR GENERATING RANDOM GRAPHS WITH PRESCRIBED DEGREES

A SEQUENTIAL IMPORTANCE SAMPLING ALGORITHM FOR GENERATING RANDOM GRAPHS WITH PRESCRIBED DEGREES. (Introduction). For example d = (2, 2, 2). Other Algorithms. 1 . Algorithms for random graphs with given degree distributions . 2 . The Pairing Model . 3 . Algorithms Based on the Pairing Model

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Sieve of Eratosthenes Quiz questions

Sieve of Eratosthenes Quiz questions. ITCS4145/5145, Parallel Programming Oct 24, 2013. When can we stop the algorithm? When the next prime is:. None of the other answers. What is the complexity of the sequential algorithm?. None of the other answers.

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Computing Betweenness Centrality for Small World Networks on a GPU

Computing Betweenness Centrality for Small World Networks on a GPU. Pushkar R. Pande Georgia Institute of Technology David A. Bader Georgia Institute of Technology. Introduction. Betweenness Centrality of a vertex is defined as, : Number of shortest paths between vertices and

197 views • 4 slides