101. Parallel Computing Class Stout s class in parallel computing. Graduate students in the Scientificcomputing program administered through LaSC (Laboratory for Scientific http://www.eecs.umich.edu/~qstout/587/

EECS 587, Parallel Computing Professor: Quentin F. Stout Parallel computers are easy to build - it's the software that takes work. Audience Typically about half the class is from Computer Science and Engineering, and half is from a wide range of other areas throughout the sciences, engineering, and medicine. Some CSE students want to become researchers in parallel computing or grid computing, while students outside CSE typically intend to apply parallel computing to their discipline, working on problems too large to be solved via standard single processor machines. Students range from seniors through postdocs, and occasionally faculty sit in on the course as well. Satisfying Degree Requirements This course can be used to satisfy requirements in a variety of degree programs. CSE Graduate Students: it satisfies general 500-level requirements for the MA and PhD. CSE Undergraduates: it satisfies "computer oriented technical elective" requirements for the CE and CS degrees. Rackam Graduate Students (other than CSE): it fulfills the cognate requirements. Graduate students in the Scientific Computing program administered through LaSC (Laboratory for Scientific Computing): it satisfies computer science distributional requirements. Most of the students in this program take this class.

102. Parallel Computing Works A book about parallel computing, focusing on a few specific research projectsdone at Caltech. http://www.netlib.org/utk/lsi/pcwLSI/text/

Next: Contents Parallel Computing Works This book describes work done at the Caltech Concurrent Computation Program , Pasadena, Califonia. This project ended in 1990 but the work has been updated in key areas until early 1994. The book also contains links to some current projects. Geoffrey C. Fox Roy D. Williams Paul C. Messina ISBN 1-55860-253-4 Morgan Kaufmann Publishers , Inc. 1994 ordering information What is Contained in Parallel Computing Works? We briefly describe the contents of this book Applications The heart of this work is a set of applications largely developed at Caltech from 1985-1990 by the Caltech Concurrent Computation Group. These are linked to a set of tables and Glossaries Application Paradigms in High Performance Fortran Algorithms and Applications in High Performance Fortran Petaflop Application Categories developed at a workshop. A table developed by Fox in 1991-1993 to categorize New York State Industrial Applications of HPCC Applications are classified into 5 problem classes: Synchronous Applications , more in I and II Such applications tend to be regular and characterised by algorithms employing simultaneous identical updates to a set of points, more in

103. LAM/MPI Parallel Computing parallel programmers, application users, and parallel computing researchers . The xmpi profiling tool and parallel debugger support (eg, http://www.lam-mpi.org/

LAM/MPI Parallel Computing Home Download Documentation FAQ ... License LAM/MPI: Enabling Efficient and Productive MPI Development LAM/MPI is a high-quality open-source implementation of the Message Passing Interface specification, including all of MPI-1.2 and much of MPI-2. Intended for production as well as research use, LAM/MPI includes a rich set of features for system administrators, parallel programmers, application users, and parallel computing researchers. Cluster Friendly, Grid Capable From its beginnings, LAM/MPI was designed to operate on heterogeneous clusters. With support for Globus and Interoperable MPI , LAM/MPI can span clusters of clusters. Performance Several transport layers, including Myrinet, are supported by LAM/MPI. With TCP/IP, LAM imposes virtually no communication overhead, even at gigabit Ethernet speeds. New collective algorithms exploit hierarchical parallelism in SMP clusters. Empowering Developers The xmpi profiling tool and parallel debugger support (e.g., using TotalView or the Distributed Debugging Tool A Stable Extensible Platform for Research Tools and Third Party Applications Since LAM/MPI implements the specified MPI standard, most

104. HPJava Home Page HPJava is an environment for scientific and parallel programming using Java. memory) parallel computers especially data parallel programming using http://www.hpjava.org/

HPJava Home Page mpiJava HPJava language SC '02 demo ... Viewing these pages HPJava Home Page HPJava is an environment for scientific and parallel programming using Java. It is based on an extended version of the Java language. One feature that HPJava adds to Java is a multi-dimensional array, or multiarray , with properties similar to the arrays of Fortran. HPJava supports parallel programming on distributed memory (and shared memory) parallel computers especially data parallel programming using distributed arrays similar to those in High Performance Fortran (HPF). The HPJava language model was motivated by work on HPF during the PCRC project it captures the HPF distributed array model in special syntax, but assumes that the programmer directly calls high-level runtime functions for communication and array manipulation. HPJava is a strict extension of Java. It incorporates all of the Java language as a subset. Any ordinary Java class can be invoked from an HPJava program without recompilation. A translated and compiled HPJava program is a standard Java class file that can be executed by a distributed collection of Java Virtual Machines. Version 1.0 of the HPJava software, including translator and runtime environment was released April, 2003:

105. PARALLEL PROGRAMMING TOOLS But one thing is certain programming for parallel computers is here to stay.Indeed, developing a parallel programming environment is a priority for all http://www.sdsc.edu/GatherScatter/gsmar92/ParallelProgTools.html

PARALLEL PROGRAMMING TOOLS Subtitles: Parallel computerscubes and more To each its own node Intelligent division Parallel programming tools by Marsha Jovanovic (Marsha Jovanovic is G/S editor. Gary Hanyzewski, Jayne Keller, Booker Bense, Carl Scarbnick, Bob Leary, and Reagan Moore also contributed to this article.) With Multiple-Instruction-Multiple-Data (MIMD) computers clearing the way for record-breaking computation speeds, scientific programmers of the 90s are being pulled into the world of parallel programming. Using large numbers of fast processors, MIMD computers break computational problems into pieces of moderate size that can be processed quickly and independently. All programmers have to do is figure out how to divide the data or the workload among the processors to take best advantage of their processing power. Does it sound complicatedperhaps a bit schizophrenic? Perhaps. But one thing is certain: programming for parallel computers is here to stay. Indeed, developing a parallel programming environment is a priority for all the NSF supercomputer centers. SDSC scientists and programmer/analysts already are working themselves through the parallel programming maze (see "The parallelization of MOPAC" in this issue for a detailed example and "Running in parallel" in G/S January-February for more about the SDSC parallel processing effort in general). This article tells you something about the programming problem and introduces you to some of the parallel programming tools available at SDSC.

106. Distributed Parallel Computing With Web Services @ SOA WEB SERVICES JOURNAL At the same time, distributed parallel computing is becoming the de facto A simple control master program could generate slave/worker services executing http://webservices.sys-con.com/read/48036.htm

Jump to a SYS-CON Magazine .NET Developer's Journal - .NETDJ ColdFusion Developer's Journal - CFDJ Eclipse Developer's Journal - EDJ Enterprise Open Source Magazine - EOS IT Solutions Guide - ITSG Java Developer's Journal - JDJ LinuxWorld Magazine - LW Macromedia MX Developer's Journal - MXDJ PowerBuilder Developer's Journal - PBDJ SEO / SEM (Search) Journal - SJ SOA Web Services Journal - WSJ Symbian Developer's Journal - SDJ WebLogic Developer's Journal - WLDJ WebSphere Journal - WJ XML-Journal - XMLJ Sign-In Register YOUR FEEDBACK Secrets Of The Masters: Core Java Interview Questions sudhansu.swain wrote: i want to java interview question Sep. 24, 2005 05:13 PM .NETDJ Editor Jon Box Responds To Calvin Austin in His Blog James Brockman wrote: >> Yes, MSDN subscriptions are NOT free. However, the .NET framework is... Sep. 24, 2005 12:40 PM Distributed Parallel Computing with Web Services Joe Smith wrote: Agreed this article is a total waste. Wonder if the product is a waste as well. Did You Read Today's Front Page Stories at SYS-CON?

107. PVM: Parallel Virtual Machine PVM enables users to exploit their existing computer hardware to solve much larger Xmdb parallel programming and debugging trainer for beginners http://www.epm.ornl.gov/pvm/pvm_home.html

PVM (Parallel Virtual Machine) is a software package that permits a heterogeneous collection of Unix and/or Windows computers hooked together by a network to be used as a single large parallel computer. Thus large computational problems can be solved more cost effectively by using the aggregate power and memory of many computers. The software is very portable. The source, which is available free thru netlib, has been compiled on everything from laptops to CRAYs. PVM enables users to exploit their existing computer hardware to solve much larger problems at minimal additional cost. Hundreds of sites around the world are using PVM to solve important scientific, industrial, and medical problems in addition to PVM's use as an educational tool to teach parallel programming. With tens of thousands of users, PVM has become the de facto standard for distributed computing world-wide. For those who need to know, PVM is Y2K compliant. PVM does not use the date anywhere in its internals. Current PVM News: EuroPVM-MPI 2005 . The 12th European PVM-MPI Meeting will be held in Capri-Sorrento Penisular, Italy

108. Introduction To Parallel Computing Motivating parallelism; Scope of parallel computing; Organization and Contentsof the Sources of Overhead in parallel Programs; Performance Metrics for http://www-users.cs.umn.edu/~karypis/parbook/

Introduction to Parallel Computing. Ananth Grama, Purdue University, W. Lafayette, IN 47906 (ayg@cs.purdue.edu Anshul Gupta, IBM T.J. Watson Research Center, Yorktown Heights, NY 10598 (anshul@watson.ibm.com George Karypis, University of Minnesota, Minneapolis, MN 55455 (karypis@cs.umn.edu Vipin Kumar, University of Minnesota, Minneapolis, MN 55455 (kumar@cs.umn.edu Follow this link for a recent review of the book published at IEEE Distributed Systems Online. Solutions to Selected Problems The solutions are password protected and are only available to lecturers at academic institutions. Click here to apply for a password. Click here to download the solutions (PDF File). Table of Contents ( PDF file PART I: BASIC CONCEPTS 1. Introduction (figures: [ PDF PS Motivating Parallelism Scope of Parallel Computing Organization and Contents of the Text 2. Parallel Programming Platforms (figures: [ PPT PDF PS (GK lecture slides [ PDF ]) (AG lecture slides [ PPT PDF PS Implicit Parallelism: Trends in Microprocessor Architectures Limitations of Memory System Performance Dichotomy of Parallel Computing Platforms Physical Organization of Parallel Platforms Communication Costs in Parallel Machines Routing Mechanisms for Interconnection Networks Impact of Process-Processor Mapping and Mapping Techniques Bibliographic Remarks 3. Principles of Parallel Algorithm Design (figures: [

109. Recent Papers By Larry Carter B., L. Carter, and J. Ferrante, ``Modeling parallel Computers as MemoryHierarchies, programming Models for Massively parallel Computers , Giloi, WK, http://www-cse.ucsd.edu/users/carter/ppbib.html

Recent paper by Larry Carter S. Nandy, L. Carter, and J. Ferrante, "Guard: Gossip Used for Autonomous Resource Detection" , IEEE International Parallel and Distributed Processing Symposium (IPDPS'05). S. Nandy, L. Carter, and J. Ferrante, "A-FAST: Autonomous Flow Approach to Scheduling Tasks" , International Conference in High-Performance Computing (HiPC'04), published in Springer LNCS 3296, pp 363-374 (2004). C. Banino, O. Beaumont, L. Carter, J. Ferrante, A. Legrand, and Y. Robert, "Scheduling Strategies for Master-Slave Tasking on Heterogeneous Processor Platforms", IEEE Transactions on Parallel and Distributed Systems, Volume 15, Number 4, pages 319-330. (April, 2004) B. Kreaseck, L. Carter, H. Casanova, and J. Ferrante, "On the Interference of Communication on Computation in Java" , Third International Workshop on Performance Modeling, Evaluation, and Optimization of Parallel and Distributed Systems (PMEO'04). M. Mills Strout, L. Carter, J. Ferrante, and B. Kreaseck, "Sparse Tiling for Stationary Iterative Methods", International Journal of High-Performance Computing Applications, Volume 18, Number 1, pages 95-113. (2004) M. Mills Strout, L. Carter, and J. Ferrante

110. 520.428 Introduction To Algorithms For Parallel Computers programming projects will be given for the IBM SP parallel computer and otheravailable departmental multicomputers. Prerequisite 520.428 or equivalent and http://www.ece.jhu.edu/~ljpodra/520.429.description.htm

Principles of Parallel Programming Department: Dept. of Electrical and Computer Engineering Meeting Times: Tuesday, Wednesday 4-5:15, Barton 225 Instructor: Dr. Louis J. Podrazik, e-mail: podrazik@super.org Office Hours: by appointment Credits: Synopsis: Programming models and languages for current computing platforms. Computational models include shared and distributed memory multiprocessors. Essential techniques of message-passing parallel programming will be based upon MPI (Message Passing Interface); shared memory programming will use the OpenMP standard. Other parallel language extensions will be studied, including Split-C and UPC (unified parallel C). Programming projects will be given for the IBM SP parallel computer and other available departmental multicomputers. Prerequisite : 520.428 or equivalent and a course in C programming. Curriculum: Course Grading Homework Assignments Course Projects Curriculum: Week 1. Overview of parallel computation and programming Week 2. JHU computing platforms Week 3.

111. PARA'02 Conference Home Page advanced program development, and tools in parallel computing. Registrationfor the PARA 02 Conference on Applied parallel computing on June 1518, http://www.csc.fi/para2002/index.phtml

Main Sponsor: Sponsors: Conference on Applied Parallel Computing 3rd CSC Scientific Meeting 15 - 18 June 2002, Dipoli Congress Centre, Espoo, Finland Note: The PARA'02 conference is over. These pages are provided for historical and reference purposes. The conference presentations are now available in video recordings here . To view the video files you will need a suitable media player in your browser: MPEG-1 player or Real-player Also the conference proceedings are now available online (click the icon). They are published in the Springer series Lecture notes in Computer Science. J. Fagerholm, J. Haataja, J. Järvinen, M. Lyly, P. Råback, V. Savolainen (Eds.): Applied Parallel Computing Advanced Scientific Computing 6th International Conference, PARA 2002, Espoo, Finland, June 15-18, 2002. Proceedings LNCS 2367 CSC - Scientific Computing Ltd. will host the sixth International Conference on Applied Parallel Computing on June 15-18, 2002. The general theme of the conference is advanced scientific computing. The conference demonstrates the ability of advanced scientific computing to solve "real-world" problems, and highlights methods, instruments, and trends in future scientific computing. The conference begins with a one-day tutorial session on grid programming.

112. Caltech Computer Science Technical Reports - Programming Parallel Computers Chandy, K. Mani (1988) programming parallel Computers. Technical Report.California Institute of Technology. CaltechCSTR1988.cstr-88-16 http://caltechcstr.library.caltech.edu/47/

Caltech Computer Science Technical Reports Main About Browse Search ... Help Programming Parallel Computers Chandy, K. Mani Programming Parallel Computers. Technical Report California Institute of Technology CaltechCSTR:1988.cs-tr-88-16 Full text available as: Postscript - Requires a viewer, such as GhostView Abstract This paper is from a keynote address to the IEEE International Conference on Computer Languages, October 9, 1988. Keynote addresses are expected to be provocative (and perhaps even entertaining), but not necessarily scholarly. The reader should be warned that this talk was prepared with these expectations in mind.Parallel computers offer the potential of great speed at low cost. The promise of parallelism is limited by the ability to program parallel machines effectively. This paper explores the opportunities and the problems of parallel computing. Technological and economic trends are studied with a view towards determining where the field of parallel computing is going. An approach to parallel programming, called UNITY, is described. UNITY was developed by Jay Misra and myself, and is described in [Chandy]. Extensions to UNITY are discussed; these extensions were motivated by discussions with Chuck Seitz EPrint Type: Monograph (Technical Report) Subjects: All Records ID Code: Deposited By: Caltech Library System Deposited On: 24 April 2001 Record Number: CaltechCSTR:1988.cs-tr-88-16

113. Parallel Algorithms And Programs We focus on transformation of parallel algorithms and programs on the PRAM to Shared Memory in programming Models For Massively parallel Computers, pp. http://i44www.info.uni-karlsruhe.de/~zimmer/parallel.html

Parallel Algorithms and Programs Today, there is a great variety on parallel algorithms for shared-memory architectures, mainly the PRAM. However, the PRAM model does not take into account properties of realistic architectures. Recently, Culler et al. defined a new more realistic machine model which reflects better the practical behaviour of massively parallel computers. Their LogP model differs from the PRAM in the following points. First, the synchronous execution is dropped. Instead all processors perform their computation asynchronously. Second, there is no shared memory assumption. Instead they consider a communication latency, communication overhead and network bandwith. Finally, the number of processors is fixed and cannot increase with the problem size. We focus on transformation of parallel algorithms and programs on the PRAM to equivalent LogP-programs. Recent research of mine: W. Zimmermann and H. Kumm: On the Implementation of Virtual Shared Memory in: Programming Models For Massively Parallel Computers, pp. 172-178, IEEE, 1993 W. Zimmermann and W. Loewe:

114. Parallel Computing, Volume 22 Bruno Lang parallel Reduction of Banded Matrices to Bidiagonal Form. ClemensAugust Thole, Owen Thomas Industrial parallel computing with Real Codes. http://www.informatik.uni-trier.de/~ley/db/journals/pc/pc22.html

Parallel Computing , Volume 22 Volume 22, Number 1, January 1996 Bruno Lang : Parallel Reduction of Banded Matrices to Bidiagonal Form. 1-18 BibTeX Margarita Amor Emilio L. Zapata : FFTs on Mesh Connected Computers. 19-38 BibTeX S. A. Savari Dimitri P. Bertsekas : Finite Termination of Asynchronous Iterative Algorithms. 39-56 BibTeX Eric de Sturler : A Performance Model for Krylov Subspace Methods on Mesh-Based Parallel Computers. 57-74 BibTeX Short Communications Himanshu Gupta P. Sadayappan : Communication-Efficient Matrix Multiplication on Hypercubes. 75-99 BibTeX A. Baronio Fabiana Zama : A Domain Decomposition Technique for Spline Image Restoration on Distributed Memory Systems. 101-110 BibTeX Practical Aspects and Experiences Donald Dabdub John H. Seinfeld : Parallel Computation in Atmospheric Chemical Modeling. 111-130 BibTeX Rolf Hempel Robin Calkin Reinhold Hess ... U. Keller : Real Applications on the New Parallel System NEC Cenju-3. 131-148 BibTeX Andreas Uhl : Wavelet Packet Best Basis Selection on Moderate Parallel MIMD Architectures. 149-158 BibTeX Volume 22, Number 2, February 1996

115. Programming Of Parallel Computers programming of parallel Computers HPB Distance course 2004.( http//www.it.uu.se/edu/course/homepage/algpar1/dist04/ ). Teacher Jarmo Rantakokko http://www.it.uu.se/edu/course/homepage/algpar1/dist04/

Department of Information Technology Jarmo Rantakokko Programming of parallel computers HPB Literature ... News Uppsala University Department of Information Technology Scientific Computing Programming of Parallel Computers Programming of Parallel Computers HPB Distance course 2004 ( http://www.it.uu.se/edu/course/homepage/algpar1/dist04/ ) Teacher Jarmo Rantakokko Room 2339, Tel: 018 - 471 2977 Aims of the course Computer simulations are used extensively both in industry and in academia. The demand for computing power is increasing faster and faster. To meet the demands parallel computers are becoming popular. Today, a powerful PC often contains two processors and it is easy to connect several PCs to a cluster, a powerful parallel computer. At the same time it is more difficult for the programmer to exploit the full capacity of the computer. The aims of the course are to give basic knowledge in parallel computers, algorithms and programming. To give knowledge in fundamental numerical algorithms and software for different parallel computers. To give skills in parallel programming. Course content Classification of parallel computers. Different forms of memory organisation and program control. Different forms of parallelism. Programming models; programming in a local name space using MPI and in global name space using OpenMP. Data partitioning and load balancing algorithms. Measurements of performance; speedup, efficiency, flops. Parallelization of fundamental algorithms in numerical linear algebra; matrix-vector and matrix-matrix multiplication. Parallel sorting and searching. Software for parallel computers. GRID computing.

116. Alibris: Computers Programming Parallel Used, new outof-print books with subject Computers programming parallel.Offering over 50 million titles from thousands of booksellers worldwide. http://www.alibris.com/search/books/subject/Computers Programming Parallel

You'll find it at Alibris! Log in here Over 50 million used, new and out-of-print books! CART ACCOUNT WISHLIST HELP ... SEARCH search in Books Music: All CD Vinyl Movies: All DVD VHS by title / ISBN by author / artist by subject / genre my email address unsubscribe here your shopping cart order status wish list ... help browse BOOKS Your search: Books Subject: Computers Programming Parallel (80 matching titles) Narrow your results by: Eligible for FREE shipping Narrow results by title Narrow results by author Narrow results by subject Narrow results by keyword Narrow results by publisher or refine further Sometimes it pays off to expand your search to view all available copies of books matching your search terms. Page of 4 sort results by Top-Selling Used Price New Price Title Author Introduction to Parallel Computing more books like this by Grama, Ananth, and Gupta, Anshul, and Karypis, George This book provides a basic, in-depth look at techniques for the design and analysis of parallel algorithms and for programming them on commercially available parallel platforms. Principles of parallel algorithms design and different parallel programming models are both discussed, with extensive coverage of MPI, POSIX threads, and Open MP. This... see all copies from new only from SVS Oracle Parallel Processing more books like this by Mahapatra, Tushar, and Mishra, Sanjay

117. Coarse-Grain Dataflow Programming Of Conventional Parallel Granular Lucid or GLU is a coarse grain dataflow language for programmingconventional parallel computers. It is based on Lucid circa which is an implicitly http://citeseer.ist.psu.edu/jagannathan95coarsegrain.html

118. ESPRIT Project ParForce (EP 6707) ParForCE (EP 6707). parallel Formal computing Environment Finally, the projectalso includes a working group on parallel program development. http://clip.dia.fi.upm.es/Projects/ParForce/parforce.html

The CLIP Group DIA FIM UPM ParForCE (EP 6707) Parallel Formal Computing Environment The ParForCE Project Technology Transfer Workshop Madrid, Spain, January 15-16 1996 Project Information This brief information corresponds to the project synopsis. Detailed descriptions of the research are found in the deliverables of the first year , the deliverables of the second year and the deliverables of the third year . You can also read a project description and report on achievements , which appeared in the EATCS bulletin in 1995 (an older version which appeared in the EATCS bulletin in 1994 can be found here Work area : Parallel Computing and Architectures COORDINATOR CLIP group, Department of Artificial Intelligence, E-28660 Boadilla del Monte, Madrid, SPAIN PARTNERS ECRC (Germany) INRIA, Institut National de Recherche en Informatique et en Automatique (France) Università di Pisa (Italy) Swedish Institute of Computer Science (Sweden) University of Southampton (United Kingdom) University of Bristol (United Kingdom) CONTACT POINT Prof. Manuel Hermenegildo

119. Practicum Structured Programming - Modula2 Exercises, tips, syntax reference, programs written in Modula2. Free Universityof Brussels. http://parallel.vub.ac.be/education/modula2/

Practicum Structured Programming Modula-2 This is the homepage of the exercises part of J. Tiberghien 's course " Programming Concepts ". Information about the theory can be found on the Info Department website. Assistants: Jan Lemeire: jan.lemeire@vub.ac.be 4k227 tel: (02/629) 2997 Arnout Swinnen aswinnen@vub.ac.be 4k226 tel: (02/629) 2493 Johan Parent johan@info.vub.ac.be Students: 1e bachelor burgerlijk ingenieur Oefeningen Project en Practicum Examen 1e bachelor burgerlijk ingenieur-architekt Oefeningen en Practicum Examen GAS students exercises Demo's Check our students projects page!! Consult freely our Documentation Technology pages Compiler Modula2 compiler installation for Windows (XDS 2.32): Download XDS 2.51 from Excelsior website +Topspeed TSCP add-on zie technology pagina or good old XDS 2.32 READ THIS BEFORE INSTALLATION: Install folder don't install XDS under "Program Files" or another folder with a space in its name!!! (create for example a folder /XDS) never use a folder with a space in its name! XDS doesn't understand this and gets mixed up. Update your version of XDS: just reinstall the new XDS in the same folder and overwrite the old folder also reinstall the topspeed package!

120. Parallel A generation in a run of parallel genetic programming may be of any length, Building a parallel computer system for $18000 that performs a half http://www.genetic-programming.com/parallel.html

Asynchronous "Island" Approach to Parallelization of Genetic Programming Techniques of "blank slate" automated learning generally require considerable computational resources to solve non-trivial problems of interest. As they say, "computer time is the mother's milk of automated learning." Increases in computing power can be realized in two ways: either by using a faster computer or by parallelizing the application. The first approach is aided by the fact that computer speeds have approximately doubled every 18 months in accordance with Moore’s law and are expected to continue to do so. The second approach (i.e., parallelization) is available for applications that can be parallelized efficiently. Genetic algorithms, genetic programming, and other techniques of evolutionary computation are highly amenable to parallelization (at essentially 100% efficiency). A run of genetic programming begins with the initial creation of individuals for the population. Then, on each generation of the run, the fitness of each individual in the population is evaluated. Then, on each generation, individuals are selected (probabilistically based on fitness) to participate in the genetic operations (e.g., reproduction, crossover, mutation, and architecture-altering operations). These three steps (i.e., fitness evaluation, Darwinian selection, and genetic operations) are iteratively performed over many generations until the termination criterion for the run is satisfied. Typically, the best single individual obtained during the run is designated as the result of the run.

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