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