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.1=..Parallel computing programming paradigms - software and problems - abstract.
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.2=..Data parallelism as a universal source of parallelism.
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.3=..What is data parallelism or domain decomposition.
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.4=..Three examples of data parallelism - regular finite difference, particle dynamics, computer chess.
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.5=..Two more examples of data parallelism - irregular finite elements, multi-target tracking.
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.6=..Structures of problems and parallel software approaches.
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.7=..Theory, modeling and computation as mappings between complex systems.
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.8=..Five problem architectures.
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.9=..Regular synchronous problem architecture.
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10=..Irregular loosely synchronous problem.
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11=..Asynchronous problem architecture.
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12=..The metaproblem architecture - an example of agile manufacturing.
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13=..Multidisciplinary analysis and design (Some of the components of agile manufacturing) - mapping of a metaproblem onto a metacomputer.
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14=..Further examples of metaproblems - Atmospheric science and computational electromagnetics.
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15=..BMC3IS and decision support - a dual use metaproblem.
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16=..The heterogeneous metaproblem components for command and control.
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17=..Which of the five problem architectures does high performance FORTRAN support.
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18=..A reminder of the five problem architectures.
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19=..
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20=..Table mapping problem classes into appropriate parallel computer architectures.
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21=..Layers of software and the stages in mapping problems onto computers.
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22=..The concept of complex systems as the basis of a theory of computing.
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23=..Parallel computing is ÒjustÓ an optimization problem.
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24=..Complex systems in the strategies of mapping problems onto computers.
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25=..From problem to specification to layered software; examples of five classes of complex systems.
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26=..Categories of industrial applications of parallel computing - abbreviations used in tables.
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27=..Industrial applications 1-5 of parallel computing.
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28=..Industrial applications 6-12 of parallel computing.
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29=..Industrial applications 12-17 of parallel computing.
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30=..Issues in parallel computing software.
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31=..Conclusions of May 1993 Pittsburgh grand challenge meeting.
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32=..What does one need to know about problem structure to produce good parallel software?
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33=..Components of software systems for distributed memory parallel computers - I - O/S, I/O, debugging.
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34=..Components of software systems for distributed memory parallel computers - II - advantages and disadvantages.
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35=..Contrasts between parallel and distributed computing.
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36=..Portable scalable languages.
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37=..Why extend existing sequential languages - FORTRAN, C.
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38=..FORTRAN or C plus message passing - Features.
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39=..FORTRAN or C plus message passing - Advantages and disadvantages.
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40=..Data parallel FORTRAN - Features.
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41=..Data parallel FORTRAN (C, C++, ADA, LISP) - advantages and disadvantages.
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42=..Architecture of Virtual machine (programming model) versus architecture of real machine.
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43=..What software systems are suitable for what problem architectures.
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44=..Software systems and problem characteristics for synchronous and asynchronous problem architectures.
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45=..Software systems and problem characteristics for loosely synchronous problem architectures.
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46=..Possible programming paradigms and software systems for the five problem architectures.
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47=..A two dimensional plot of temporal and spatial problem characteristics labeled by natural computer architecture.
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48=..Two types of parallel extensions to FORTRAN and C.
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49=..
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50=..Motivation and inputs to the design of HPF language.
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51=..What problem features should a complete parallel software system include - which can HPF express.
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52=..What are possible features in an extended high performance FORTRAN HPF+.
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53=..Table summarizing HPF features and extensions HPF+ for some application classes.
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54=..Some synchronous problems expressible in HPF - I.
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55=..Some synchronous problems expressible in HPF - II.
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56=..Some embarrassingly parallel problems expressible in HPF.
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57=..Loosely synchronous problems expressible in HPF - Molecular dynamics and unstructured finite elements.
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58=..Region Identification in image processing and HPF.
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59=..Clustering algorithms for statistical physics and HPF.
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60=..Clustering in a spin system simulation near a critical point.
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61=..Some multiphase loosely synchronous problems which need HPF extensions.
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62=..Multiphase problem examples - particle in the cell, irregularly coupled structured meshes.
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63=..Very hard loosely synchronous problems for extended HPF - direct sparse matrix solution, fast multipole for particle dynamics.
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64=..Overview of O(N log N) parallel Barnes Hut algorithms for astrophysical particle dynamics.
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65=..Example of the Barnes-Hut tree.
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66=..Parallel Simulation of cosmological model 8,000,000 Òparticles.
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67=..137,000 object galaxy formed in parallel simulation of cosmological model.
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68=..Speed up of Barnes-Hut algorithm on 1-512 node nCUBE-1 as function of number of particles.
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69=..Summary of issues in the relation of problem (Virtual Machine) and computer architectures and associated programming paradigms.
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70=..What should a good parallel language express?
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71=..The map of problem onto computer performed in two or three stages.
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72=..Problem and machine architectures and message passing programming paradigms.
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73=..Real and virtual machines viewed as tightly coupled sparsely connected complex systems.
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74=..Real and virtual machines viewed as loosely coupled fully connected complex systems
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75=..Different virtual machines used by HPF computer and HPF interpreter.
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76=..Software integration - coarse grain task parallelism - metaproblems - use of AVS.
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77=..Issues in using AVS for general coarse grain software integration.
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78=..A generic AVS dataflow environment implemented on a distributed heterogeneous computing network.
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79=..Stock option price modeling as a case study in use of AVS for software integration - summary.
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80=..CM-5, DECmpp and workstation network integrated with AVS for stock option pricing.
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81=..The AVS front end for previous simulation.
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82=..The AVS front end for computational electromagnetic (CEM) distributed simulation.
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83=..Computational electromagnetism as an AVS case study - summary.
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84=..The EM scattering problem and physical parameters for system components.
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85=..The HPFDC (High Performance Distributed Computing) network and the decomposition of CEM into modules.
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86=..CEM modules decomposed over the HPDC network.
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87=..AVS front end for the NASA data assimilation grand challenge - Kalmar filters to combine weather data and models.
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88=..The HPDC network for data assimilation and the decomposition of problem components.
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89=..Summary of outstanding issues in programming paradigms.
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90=..HPANDF and common data parallelism for FORTRAN, C, C++, ADA.
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91=..Metaproblems versus metacomputers - high level or low level virtual machine.
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92=..Some issues in functionality needed by software integration systems.
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93=..AVS v. PVM . PVM v. MPI v. Multimedia data transport standards.
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94=..FORTRAN-M v. AVS. Should task parallelism be integrated into language.