Pram models, chapter 6 in parallel and distributed computing handbook, edited by a. Parallel algorithms we will focus our attention on the design and analysis of e. Thus, if an algorithm designed for a pram model or any other model can be translated to an algorithm that runs e. Here, multiple processors are attached to a single block of memory. In spite of this difficulty, useful parallel models have emerged, along with a deeper understanding of the modeling process. Pram can access any address of the shared memory in a time unit. Parallel and distributed computing pram algorithms. Total number of steps in parallel algorithm is equal to the number.
Worktime presentation framework of parallel algorithms. However, since the pram requires a shared memory that can be accessed by all processors at the same time, it is not. Siam journal on computing society for industrial and. Cost of a pram computation is the product of the parallel time complexity and the number of processors used. As an example, consider the widelyused parallel randomaccess machine pram model. Optimal parallel algorithms for computing the sum, the. This second edition is a revision of designing efficient algorithms for parallel computers. Space complexity the number of shared memory cells accessed. Allows parallelalgorithm designers to treat processing power as unlimited. For test the parallel algorithm were used the following number of cores.
In other words, if you cant get a good parallel algorithm on the pram model, youre not going to get a good parallel algorithm in the real world. How does parallel programming affect an algorithms time. Here, n number of processors can perform independent operations on n number of data in a. We abandon attempts to force sequential algorithms into parallel environments for such attempts usually result in transforming a good uniprocessor algorithm into ahopclcssly greecly parallel algorithm. It has been a tradition of computer science to describe serial algorithms in abstract machine models, often the one known as randomaccess machine. Complexity measures for mapreduce, and comparison to. As the name suggests, the pram model is an extension of the familiar ram model of sequential computation that is used in algorithm analysis. Parallel random access machines pram is a model, which is considered for most of the parallel algorithms. The author has discarded chapters on logic programming and pipeline vector processors, updated and enhanced the remaining material, and added chapters of pram algorithms, mapping and scheduling, and parallel imperative. Fast scheduling algorithms on parallel computers by david hclmbold and lhst mayr department of computer science.
Embedding quality metrics dilation maximum number of lines an edge is mapped to congestion maximum number of edges mapped on a single link. This tutorial provides an introduction to the design and analysis of. This article discusses the analysis of parallel algorithms. Many algorithms for other models such as the network model can be derived directly from pram algorithms. Digression 1 in the following, we will use the words vector and matrix to denote the usual linearalgebraic entities, and the word sequencefor a linear list. The pram model of parallel computation parallel random access machine pram natural extension of ram. Pdf practical pram programming download ebook for free. Pram algorithms parallel random access machine pram. Algorithms in which several operations may be executed simultaneously are referred to as parallel algorithms. A large body of work exists which already addresses large scale high performance computing hpc performance of parallel graph. Written by world experts on this technology, it explains how to use pram to design algorithms for parallel computers and includes a number of pram implementations. This paper contributes to the understanding of parallel graph algorithm performance on a scale that more closely resembles a desktop environment. If the originaltree has nnodes, allother steps take olog n.
The pram incorporates the basic elements of a parallel machine and has the property that an algorithm. We reserve the word arrayfor the familiar concretedata structure that is used to. It mentions zebra networks and rat algorithms, along with more mundane computers such. Parallel random access machine pram pram algorithms p. Optimal parallel algorithms for computing the sum, the pre. The pram is a good parallel computing model in the sense that parallelism of each problem can be revealed by the performance of parallel algorithms on the pram. The loop is done in constant time on n2 processors in parallel. In recent years, there has been an explosive growth in the availability and diversity of parallel processors for computation. In parallel computing, amdahls law is mainly used to predict the theoretical maximum speedup for program processing using multiple processors. A parallel algorithm can be executed simultaneously on many different processing devices and then combined together to get the correct result. An optimal randomized parallel algorithm for finding. Parallel algorithms the parallel algorithms usually divide the problem into more symmetrical or asymmetrical subproblems and pass them to many processors and put the results back together at one end. We discuss multiple optimization techniques that reduce communication volume as well as loadbalance the algorithm. These paradigms make it possible to discover and exploit the parallelism inherent in many classical graph problems.
Background the socalled pram for parallel randomaccess machine, or model parallel algorithmic theory has been widely embraced by the computer science theory and algorithms communities, as a generalpurpose approach to parallel algorithms. In addition, it explains the models followed in parallel algorithms, their structures, and implementation. Parallel algorithms cmu school of computer science carnegie. Note that a pram assumes that each processing unit has o1 local storage and thus pram is not the best t for capturing modern parallel computing clusters. Think parallel and pram all operations synchronized, same speed, p i. A full online course on parallel algorithms coupled with xmtc programming assignments. Oct 02, 2012 parallel algorithms the parallel algorithms usually divide the problem into more symmetrical or asymmetrical subproblems and pass them to many processors and put the results back together at one end. Google scholar digital library cz89 richard cole and ofer zajicek. The pram model and algorithms computer science, fsu. In this paper we first, consider schedulingproblems given by. Parallel and distributed computing pram algorithms, authorsiddhartha chatterjee and jan prins, year2002. Ieee transactions on parallel and distributed systems 16.
Pdf on jan 1, 2008, henri casanova and others published parallel algorithms find. The resource consumption in parallel algorithms is both processor cycles on each processor and also the communication overhead between the processors. Index terms connection machine, parallel algorithms, par allel computing, pram, prefix computations, scan. A more practical pram model proceedings of the first. Chapters 1 and 2 cover two classical theoretical models of parallel com putation. All five algorithms have been tested, and the radix sort is the currently supported sorting algorithm for the connection machine. Similarly, many computer science researchers have used a socalled parallel randomaccess. Assumptions made in pram model for ideal parallelism can. Contents preface xiii list of acronyms xix 1 introduction 1 1. The history of parallel computing goes back far in the past, where the current interest in gpu computing was not yet predictable. Parallel algorithms chapters 4 6, and scheduling chapters 78. While not a standard book, the notes for this tutorial are essentially a book. Some important concepts date back to that time, with lots of theoretical activity between 1980 and 1990. If we denote the speed up by s then amdahls law is.
Some basic dataparallel algorithms and techniques, 104 pages pdf, class notes of courses on parallel algorithms taught since 1992 at the university of maryland, college park, tel aviv university and the technion. Parallel algorithms a simple model for parallel processing pram. Abstract pdf 3444 kb 1996 optimal parallel algorithm for brooks colouring bounded degree graphs in logarithmic time on erew pram. Like in the analysis of ordinary, sequential, algorithms, one is typically interested in asymptotic bounds on the resource consumption mainly time spent computing, but the analysis is performed in the presence of multiple processor units that cooperate to perform computations.
The pram model focuses exclusively on concurrency issues and explicitly ignores issues of synchronization and communication. Although pram parallel random access memory is a wellknown topic in parallel computing, its practical application has rarely been explored. Evolving concerns for parallel algorithms, a talk about the evolution of goalsconcerns of parallel models and algorithms, including cellular automata, mesh connected computers, reconfigurable meshes, and powerconstrained algorithms for mesh connected computers. The pram model and algorithms florida state university. The main methodological goal of these notes is to cope with the illde. Scans as primitive parallel operations computers, ieee.
An nprocessor pram model consists of a set of n processors all connected to a common shared memory 32, 37, 38, 77. Useful in the early days of parallel computing when topology specific algorithms were being developed. Developing a standard parallel model of computation for analyzing algorithms has proven difficult because different parallel computers tend to vary significantly in their organizations. In a single unit of time, each processor can perform an arithmetic, logical, or memory access operation. In computer science, a parallel algorithm, as opposed to a traditional serial algorithm, is an algorithm which can do multiple operations in a given time. Parallel computing pram algorithms siddhartha chatterjee jan prins fall 2015 contents. Test performed in matrices with dimensions up x, increasing with steps of 100. In the pram model, a set of processors share a single memory system. Parallel time complexity the time elapsed for p 0 s computation. The parallel algorithms in this chapter are presented in terms of one popular theoretical model. Pram is an attractive and important model for designers of parallel algorithms. Siam journal on computing siam society for industrial and. A pprocessor priority pram can be simulated by a pprocessor erew pram with time complexity increased by a factor of.
The pram model parallel random access machine pram. The mostexpensive step of the pathfinding algorithm is computing theexpanded tree. Complexity measures for mapreduce, and comparison to parallel computing ashish goel stanford university and twitter kamesh munagala duke university and twitter november 11, 2012 the programming paradigm mapreduce 3 and its main opensource implementation, hadoop 1, have had an enormous impact on large scale data processing. Many parallel algorithms for arrays, lists, trees, and graphs can be easily described in the pram model. This tutorial provides an introduction to the design and analysis of parallel algorithms.
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