41. Concurrent Programming Using Parallel Virtual Machine. Kernel and implement their concurrent programs in pvm on an IBM SP2 machine. The structure of pvm programs and different types of parallel paradigms http://digitalcommons.hil.unb.ca/dissertations/AAIMQ38398/

Home dissertations home about ... Advanced Search Concurrent programming using Parallel Virtual Machine. Soumendra Naik, The University of New Brunswick Date: 1998 Download the dissertation (PDF format) Tell a colleague about it. Printing Tips : Select 'print as image' in the Acrobat print dialog if you have trouble printing. The thesis deals with the design, development and performance evaluation of concurrent programs using Parallel Virtual Machine (PVM) software system. We consider Matrix Multiplication, Sorting, Embarrassingly Parallel Kernel and Multigrid Kernel and implement their concurrent programs in PVM on an IBM SP2 machine. The structure of PVM programs and different types of parallel paradigms such as master-slave, farming and ring for the selected applications are discussed. Strategies such as the use of barriers and groups are incorporated in the implementations to achieve synchronization of processes. We also focus on issues including the ease of development of parallel code, efficiency of remote machines with respect to ease of use, computing times, response times and other issues which affect the parallel programmer. Experiences of a remote user of a parallel computer are given to exemplify the challenges involved in using a remote machine. For the concurrent implementations, speedups ranging between 1.0-7.7 were observed for 2-8 processors. Poor speedups area attributed to the high intercommunication costs whereas the absence of any significant amount of inter-process communication and concurrcent communications between the processes account for the high speedups. Performance models are developed to describe the timings obtained on an IBM SP2. The models can be used to predict the asymptotic values of speedup and efficiency of the concurrent implementations.

42. PVM Find It Computers Parallel Computing programming Libraries pvm PVaniM Online and postmortem visualization support for pvm programs. http://www.ebroadcast.com.au/dir/Computers/Parallel_Computing/Programming/Librar

SEARCH GUIDE NEWS AUSTRALIAN TV GUIDE DVD RENTALS ... Libraries : PVM COMPUTERS Documentation PVM Official Parallel Virtual Machine site. News, documentation, source code, performance monitors, links to software written in PVM. Adsmith An object-based distributed shared memory system on PVM. Source code, papers, and documentation. CPPvm C++ message passing library based on PVM. Source code, documentation, and examples. Dome Distributed Object Migration Environment. Runs on top of PVM. Source code and papers. EasyPVM PVM bindings for C++. HP-PVM Commercial high-performance implementation of PVM. Product information and installation instructions. Internet Parallel Computing Archive : PVM3 Archive of PVM-related tools and documentation. Internet Parallel Computing Archive : Tape-PVM Event tracing tool. Source code and user manual. JPVM A message-passing library for Java similar to PVM. Source code and papers. jPVM An interface to allow Java applications to use PVM. Source code and documentation. LISP Language Bindings for PVM3 PVM bindings for Common Lisp.

43. Parallel Computing pvm is getting popular in accomplishing this sort of programming model. pvm supports programs written in C, C++, and Fortran. http://www.peterindia.net/ParallelComputing.html

Parallel Computing Abstract Introduction Message-passing PVM (Parallel Virtual Machine) ... Parallel Computing - Links Abstract In the last decade, researchers and scientists have investigated ways to leverage the power of inexpensive networked workstations for parallel applications. The Message Passing Interface (MPI) standard provides a common Application Programming Interface (API) for the development of parallel applications regardless of the type of multiprocessor system used. In the recent past, the Java programming language has made significant inroads as the programming language of choice for the development of a variety of applications in diverse domains. Having realised the significance of Java in the software developement arena, we propose to develop a reference implementation of MPI standard using Java programming language. Here we have supplied a broad overview of the most important paradigms for developing parallel applications. Introduction If we are thrusted to solve problems which are too complex with theoretical approaches and too expensive with empirical approaches, scientists turn to simulation models for solving this sort of problems. Some specific problems, such as global climate modeling demand more computational resources than a single processor machine can provide. With the cost of parallel computers outside the reach of most budgets, researchers instead form parallel supercomputers out of existing in-house workstations connected via a network.

44. PROGRAMMING LANGUAGES ************************* Name PCN From A tool for postmortem debugging of pvm programs. Allows programs to be deterministically AX window system based tool for monitoring pvm programs. http://cs-www.bu.edu/faculty/best/crs/cs551/projects/languages.txt

Desc.: XMTV is an X/Motif-based graphics client/server package that emulates a frame buffer. It is implemented on top of LAM, a UNIX cluster computing environment. It provides an easy to use, low cost alternative for run-time visualization of computation results. The XMTV client library can be used by MPI (and PVM) applications under LAM, from C and Fortran. It provides a simple interface to plot coloured data frames. The XMTV server can be run on any node in the multicomputer. The graphics calls locate and direct their requests to the proper destination.

45. Customizing Batch Jobs For LSF pvm is a parallel programming system distributed by Oak Ridge National pvm programs are controlled by a file, the pvm hosts file, that contains host http://aixdoc.urz.uni-heidelberg.de/doc_link/en_US/local/lsf.3.2/html/users/12-c

[Contents] [Index] [Top] [Bottom] ... [Next] 12. Customizing Batch Jobs for LSF This chapter describes how to customize your batch jobs to take advantage of LSF and LSF Batch features. Environment Variables When LSF Batch runs a batch job it sets several environment variables. Batch jobs can use the values of these variables to control how they execute. The environment variables set by LSF Batch are: This variable is set each time a checkpointed job is submitted. The value of the variable is chkpntdir /jobId , a subdirectory of the checkpoint directory that is specified when the job is submitted. The subdirectory is identified by the job ID of the submitted job. The LSF Batch job ID number. The full path name of the batch job file. This is a /bin/sh script on UNIX systems or a . BAT command script on Windows NT systems that invokes the batch job. The list of hosts selected by LSF Batch to run the batch job. If the job is run on a single processor, the value of is the name of the execution host. For parallel jobs, the names of all execution hosts are listed separated by spaces. The batch job file is run on the first host in the list. The name of the batch queue from which the job was dispatched.

46. The Paper Describes A Parallel Program Checkpointing Mechanism And support generic pvm programs created by the PGRADE Grid programming environment. system can guarantee the execution of any pvm program in the Grid. http://grid.ucy.ac.cy/axgrids04/AxGrids/papers/abstract.txt

The paper describes a parallel program checkpointing mechanism and its potential application in Grid systems in order to migrate applications among Grid sites. The checkpointing mechanism can automatically (without user interaction) support generic PVM programs created by the PGRADE Grid programming environment. The developed checkpointing mechanism is general enough to be used by any Grid job manager but the current implementation is connected to Condor. As a result, the integrated Condor/PGRADE system can guarantee the execution of any PVM program in the Grid. Notice that the Condor system can only guarantee the execution of sequential jobs. Integration of the Grid migration framework and the Mercury Grid monitor results in an observable Grid execution environment where the performance monitoring and visualization of PVM applications are supported even when the PVM application migrates in the

47. Math.nist.gov/~KRemington/Primer/Sample_code/spmd/ program for illustrating an c SPMD programming style. c c The first pvm of the program c endif c c Call pvmfexit to terminate the pvm program http://math.nist.gov/~KRemington/Primer/Sample_code/spmd/spmd.f.txt

48. Parallel Computing In Remote Sensing Data Processing basic programming techniques by using Linux/pvm to implement a pvm program. B.Wilkinson ad M.Allen,Parallel programming Techniques and Applications http://www.gisdevelopment.net/aars/acrs/2000/ts9/imgp0004b.shtml

Home Site Map Subscribe Newsletters Search The Site ... ACRS Sessions Water Resources Coastal Zone Monitoring Digital Photogrammetry Environment ... AirSAR/MASTER Poster Sessions Session 1 Session 2 Session 3 ACRS 2000 Image Processing Printer Friendly Format Page 3 of 3 Previous Parallel Computing in Remote Sensing Data Processing 3.1 Matrix Multiplication Results The matrix multiplication was run with forking of different umbers of tasks to demonstrate the speedup. The problem sizes were 256X256, 512X512, 768 X768, 1024X1024, and 1280X1280 in our experiments. It is well known, the speedup can be defined as ts / tp, where ts is the execution time using serial program, and tp is the execution time using multiprocessor. The execution time o dual2 (2 CPUs),dual2 ~3 (4 CPUs),dual2 ~4 (6 CPUs),dual2 ~5(8CPUs), and dual2 ~9 (16 CPUs), were listed in Figure 5, respectively.The corresponding speedup of different problem size by varying the umber of slave programs were shown in Figure 6.Since matrix multiplication was uniform workload application, the highest speedup was obtained about 10.89 (1280 ?1280)by using our SMP cluster with 16 processors. We also found that the speedups were closed when creating two slave programs o one dual processor machine a d two slaves program on two SMPs respectively. Figure 5: Execution time (sec.) of SMP cluster with different number of tasks (slave programs).

49. Parallel Computing In Remote Sensing Data Processing Several industrystandard parallel programming environments, such as pvm 5 ,MPI, and Open MP, are also available for, and are well-suited to, http://www.gisdevelopment.net/aars/acrs/2000/ts9/imgp0004pf.htm

Parallel Computing in Remote Sensing Data Processing Chao-Tung Yang *Chi-Chu Hung Associate Researcher Satellite Analyst Ground System Section National Space Program Office Hsinchu, Taiwan Tel:+886-3-5784208 ext.1563 Fax:+886-3-5779058 e-mail: ctyang@nspo.gov.tw Keywords: Parallel Computing, Clustering, Speedup, Remote Sensing Abstract There are a growing umber of people who want to use remotely sensed data and GIS data. What is needed is a large-scale processing and storage system that provides high bandwidth at low cost. Scalable computing clusters, ranging from a cluster of (homogeneous or heterogeneous) PCs or workstations, to SMPs, are rapidly becoming the standard platforms for high-performance and large-scale computing. To utilize the resources of a parallel computer, a problem had to be algorithmically expressed as comprising a set of concurrently executing sub-problems or tasks. To utilize the parallelism of cluster of SMPs, we present the basic programming techniques by using PVM to implement a message-passing program. The matrix multiplication a d parallel ray tracing problems are illustrated and the experiments are also demonstrated on our Linux SMPs cluster. The experimental results show that our Linux/PVM cluster can achieve high speedups for applications. 1 Introduction There are a growing umber of people who want to use remotely sensed data and GIS data. The different applications that they want to required increasing amounts of spatial, temporal, and spectral resolution. Some users, for example, are satisfied with a single image a day, while others require many images a hour. The ROCSAT-2 is the second space program initiated by National Space Program Once (NSPO) of National Science Council (NSC), the Republic of China. The ROCSAT-2 Satellite is a three-axis stabilized satellite to be launched by a small expendable launch vehicle into a sun-synchronous orbit. The primary goals of this mission are remote sensing applications for natural disaster evaluation, agriculture application, urban planning, environmental monitoring, and ocean surveillance over Taiwan area and its surrounding oceans.

50. LinuxQuestions.org - PVM Cluster Programming - Where Linux Users Come For Help LinuxQuestions.org offers a free Linux forum where Linux newbies can ask questions and Linux experts can offer advice. Topics include security, installation http://www.linuxquestions.org/questions/history/338955

Help answer threads with 0 replies Home Forums HCL ... Linux - Networking Author Thread (121 views) Newbie Registered: Mar 2005 Location: Distribution: Posts: 17 HCL Entries Reviews PVM Cluster Programming post #1 I have set up a network of 4 computers using PVM cluster. Now I am trying to write a program to use the capabilities of this cluster. Intially i just need to try out some exmaples and i tried using the programs in the example folder given ..... i wasnt able to understand the programs as they seem to be too complicated .... I also want to know if i could use programs written in matlab and running paralelly using PVM. Is using aimk the only way to compile the c programs as i keep getting errors when i try to do that using gcc .... Please help and suggest sharp Report this post to a moderator Logged 06:23 AM bruse Member Registered: Feb 2005 Location: delhi Distribution: mandrake Posts: 566 HCL Entries Reviews post #2 i think gcc will give error for cluster programs. so uc an try pvmgcc or mpi gcc to compile a parallel coding. and can u pls attach ur model parallel c coding...

51. Parallel Virtual Machine (PVM) - Parallel Programming While a pvm program is running there are two sorts of communication When defining a group tasks of every other pvm program running in the pvm http://parawiki.plm.eecs.uni-kassel.de/parawiki/index.php/Parallel_Virtual_Machi

Parallel Virtual Machine (PVM) From Parallel Programming Table of contents showTocToggle("show","hide") 1 History 2 Design 2.1 Virtual machine 2.2 Spawning tasks ... edit History PVM was created as a message passing system that enables a network of heterogenous (in the first versions only supported Unix) computers to be used as a single large distributed memory parallel virtual machine. The first version PVM 1.0 was created by Vaidy Sunderam and Al Geist in 1989 at the Oak Ridge National Laboratory. It was developed for internal use only and hence not released to the public. PVM was completely rewritten in 1991 at the University of Tennessee in Knoxville and released as PVM 2.0. A cleaner specification and improvements in robustness and portability were the achievements of the new version. For the third major release PVM 3.0 a complete redesign was considered necessary in order to obtain better scalability and portability. Beyond the implementation for Unix systems, PVM has now been ported to additional platforms such as Windows and Linux. Version 3 was released in March 1993. As of today the newest version is 3.4.5, which was published in September 2004. edit Design edit Virtual machine The main issue of PVM is to pretend that all machines create one virtual machine although having different architectures, memory usage and networks. This is realized by PVM daemons (pvmd). On each machine one pvmd must be started. Pvmds are responsible not only for communication. They are the central instance of task-management and communication for all PVM tasks on a machine. All communication between tasks on several machines is done via pvmds and not between the tasks directly. The first pvmd started in a network becomes the master pvmd. The master pvmd is responsible for starting the slave pvmds on the other machines in the net. Starting the master and slave pvmds is normally done by the PVM console, a bash-like command-line interpreter to manage the PVM environment. The PVM console enables users to add new hosts (with new slave pvmds) or to start (spawn) PVM programs. Instead of the usage of the PVM console, library functions are available for these tasks.

52. OSCAR - Linux Geek Net in addition to pvm s use as an educational tool to teach parallel programming. that are selected by the user for a given run of the pvm program. http://www.linuxgeek.net/index.pl/oscar

Home Print! My Account Home Linux Clusters OSCAR Site Navigation Begining Linux Bicycling Documentation FAQ ... Site Map Username Password Click here to register. September 25, 2005 Open Source Clustering Application Resource OSCAR version 1.3 is a snapshot of the best known methods for building, programming, and using clusters. It consists of a fully integrated a nd easy to install software bundle designed for high performance cluster computing. Everything needed to install, build, maintain, and use a mo dest sized Linux cluster is included in the suite, making it unnecessary to download or even install any individual software packages on your cluster. C3 is a command line interface that may also be called within programs. M3C provides a web based GUI, that among other features, may i nvoke the C3 tools. The Cluster Command and Control (C3) tool suite was developed for use in operating the HighTORC Linux cluster at Oak Ridge National Laboratorycexec - A general utility that enables the execution of any standard command on all cluster nodes cget - Retrieves files or directories from all cluster nodes ckill - Terminates a user specified process on all cluster nodes cpush - Distribute files or directories to all cluster nodes cpushimage - Update the system image on all cluster nodes using an image captured by the SystemImager tool crm - Remove files or directories from all cluster nodes cshutdown - Shutdown or restart all cluster nodes clist - List all the cluster name and type of each cluster in the configuration file

53. HITERM Deliverables: D02.2 The design of the message passing programming model pvm is shown in Figure 1. User programs written in C, C++ or Fortran access pvm through library http://www.ess.co.at/HITERM/DELIVERABLES/D02_2.html

Project On-line Deliverables: D02.2 The Parallel Environment Installation Manual (Final) Programme name: ESPRIT Domain: HPCN Project acronym: HITERM Contract number: Project title: High-Performance Computing and Networking for Technological and Environmental Risk Management Project Deliverable: Related Work Package: WP 2 Type of Deliverable: Technical Report Dissemination level: project internal Document Authors: Peter Mieth, Steffen Unger, Matthias L. Jugel, GMD Edited by: Kurt Fedra, ESS Document Version: 1.3 (Final) First Availability: Last Modification: EXECUTIVE SUMMARY The document serves as an installation guide for basic software components such as the HITERM Simulation Server and necessary basic standard software. This document also describes the different parallelization strategies for the different HITERM model modules. It explains the methodology employed and gives initial results, showing the decrease in run-time and the speed-up as a function of the CPU nodes used. The three core parts of the model system for atmospheric releases (applies equally to the surface and groundwater components): source strength determination in a Monte Carlo frame wind field computation transport calculation are parallelly implemented. In order to guarantee maximum flexibility and portability of the software, the PVM library was used. The programs run on a specially designed parallel machine such as MANNA (Giloi 1991, Garnatz 1996), as well as on a local workstation cluster running PVM (e.g. SUN, DEC, IBM, Silicon Graphics).

54. Parallel Programming With PVM Parallel programming with pvm. Philippe Marquet marquet@lifl.fr Maîtrise d informatique November 22, 1993 3 programming with pvm, the user interface http://www.lifl.fr/~marquet/ens/pp/pvm/

This document was produces by H E V E ... A Browsers should undergo some configuration to show some symbols. Refer to the H E V E ... A home page Parallel programming with PVM Philippe Marquet marquet@lifl.fr Maîtrise d'informatique November 22, 1993 minor changes, November 24, 1994 revised, December 9, 1994 revised, January 10, 1995 revised, January 7, 1996 February 1998 This document is also available as a gzip'ed PostScript file Thanks to PVM-Parallel Virtual Machine 1 Overview Major advantages of PVM Features Heterogeneity Portability ... How to get it 2 Using PVM Building PVM Installing PVM Programming concepts Starting a parallel virtual machine ... Tools 3 Programming with PVM, the user interface Introduction Process management primitives Information Dynamic configuration ... Fortran interface 4 Writing applications Hello world in C Hello world in Fortran Parallelizing applications Divide and Conquer ... The SPMD model 5 Debugging methods Debugging a PVM program Three steps in debugging PVM programs 6 Implementation details Network protocols PVM at work TidTask identifier Data conversion ... PVM version 3 7 Pros and cons Pros of PVM Cons of PVM 8 Conclusions New features of PVM 3.4

55. Using Interface Classes To Simplify Cluster (PVM And MPI) Application Programmin Listing 1 Two simple pvm programs a sending worker and a receiving worker. Each datatype that s sent or received by a pvm program has its own set of http://www.informit.com/articles/article.asp?p=354979&seqNum=3

56. PVM FAQ This is a short introduction on how to use pvm on HPCVL machines. It helps you start running your pvm programs, and show hos to submit and control pvm batch http://www.hpcvl.org/faqs/pvm/pvmGE.html

57. Running PVM Programs In this section you ll learn how to compile and run pvm programs. Later chapters of this book describe how to write parallel pvm programs. http://www.netlib.org/pvm3/book/node24.html

Next: PVM Console Details Up: Using PVM Previous: Common Startup Problems Running PVM Programs In this section you'll learn how to compile and run PVM programs. Later chapters of this book describe how to write parallel PVM programs. In this section we will work with the example programs supplied with the PVM software. These example programs make useful templates on which to base your own PVM programs. The first step is to copy the example programs into your own area: % cp -r $PVM_ROOT/examples $HOME/pvm3/examples % cd $HOME/pvm3/examples The examples directory contains a Makefile.aimk and Readme file that describe how to build the examples. PVM supplies an architecture-independent make, aimk , that automatically determines PVM_ARCH and links any operating system specific libraries to your application. aimk was automatically added to your $PATH when you placed the cshrc.stub in your .cshrc file. Using aimk allows you to leave the source code and makefile unchanged as you compile across different architectures. The master/slave programming model is the most popular model used in distributed computing. (In the general parallel programming arena, the SPMD model is more popular.) To compile the master/slave C example, type

58. PVM On The HPC pvm programs delegate their message passing requirements to pvmd the pvm Once a pvm program has been compiled, it should be placed in job script in a http://www.lancs.ac.uk/iss/hpc/pvm.html

Information Systems Services Services Home Quick links Home/Services AntiVirus Email Graphics Network Printing Remote Access Support Training Unix Video Conf. Web Resources Windows Index Registration Unix Windows Printing ... Index PVM on the HPC What is PVM? "PVM (Parallel Virtual Machine) is a portable message-passing programming system, designed to link separate host machines to form a ``virtual machine'' which is a single, manageable computing resource." - from the PVM FAQ PVM programs delegate their message passing requirements to pvmd - the PVM daemon - a copy of which must be running on every machine in the parallel environment. On the HPC, this process has been integrated into Codine/SGE, in order to simplify the process of running PVM programs, and to ensure that the machine resources are evenly distributed. Running PVM programs Once a PVM program has been compiled, it should be placed in job script in a similar manner to running simple jobs using the qsub command. An additional set of arguments is required to instruct Codine that a PVM parallel environment is required, and that a specific number of slots is requested. For example: qsub -pe pvm 4 The above would request four pvm slots on the HPC. A fuller description of the

59. The JPVM Home Page Why a Java pvm? The reasons against are obvious Java programs suffer from Developing pvm programs is typically not an easy undertaking for non-toy http://www.cs.virginia.edu/~ajf2j/jpvm.html

JPVM The Java Parallel Virtual Machine NOTE: If you are currently using JPVM, please download the latest version below (v0.2.1, released Feb.2, 1999). It contains an important bug fix to pvm_recv. JPVM is a PVM-like library of object classes implemented in and for use with the Java Programming language. PVM is a popular message passing interface used in numerous heterogeneous hardware environments ranging from distributed memory parallel machines to networks of workstations. Java is the popular object oriented programming language from Sun Microsystems that has become a hot-spot of development on the Web. JPVM, thus, is the combination of both - ease of programming inherited from Java, high performance through parallelism inherited from PVM. Why a Java PVM? The reasons against are obvious - Java programs suffer from poor performance, running more than 10 times slower than C and Fortran counterparts in a number of tests I ran on simple numerical kernels. Why then would anyone want to do parallel programming in Java? The answer for me lies in a combination of issues including the difficulty of programming - parallel programming in particular, the increasing gap between CPU and communications performance, and the increasing availability of idle workstations. Developing PVM programs is typically not an easy undertaking for non-toy problems. The available language bindings for PVM (i.e., Fortran, C, and even C++) don't make matters any easier. Java has been found to be easy to learn and scalable to complex programming problems, and thus might help avoid some of the incidental complexity in PVM programming, and allow the programmer to concentrate on the inherent complexity - there's enough of that to go around.

60. PVM Implementations Of Fx And Archimedes to make minor (Paragon) to major (T3D) modifications to run pvm programs on MPPs. The details of running pvm programs are hard to hide from users. http://www-2.cs.cmu.edu/afs/cs/project/nectar-adamb/pvm95/fxandarch.html

PVM Implementations of Fx and Archimedes Talk Abstract pdinda@cs.cmu.edu Ports by: David R. O'Hallaron (Archimedes) Introduction This talk discusses two parallel compiler systems that were ported from the iWarp supercomputer to PVM , and our experiences with PVM as a compiler target and a user vehicle. The first of these systems, Fx , compiles a variant of High Performance Fortran ( HPF ) while the second, Archimedes , compiles finite element method codes. In general, we found PVM was an easy environment to port to, but at the cost of performance. PVM was considerably slower than the native communication system on each of the machines we looked at (DEC Alphas with Ethernet, FDDI, and HiPPI, Intel Paragon, Cray T3D). Much of this slowdown is probably due to the extra copying needed to provide PVM's programmer-friendly semantics, which, as compiler-writers, are unnecessary to us. Although PVM goes a long way to making parallel programs portable, we found it was necessary to make minor (Paragon) to major (T3D) modifications to run PVM programs on MPPs. The details of running PVM programs are hard to hide from users. Although our toolchain hides the details of compiling and linking for PVM, once an executable is produced, the user is left to deal with hostfiles, daemons, and other details of execution - issues that are nonexistent under the operating systems of MPPs.

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