Table of Contents for Methodology of Computational Science

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1 Methodology of Computational Science
2 Abstract of Methodology of Computational Science Presentation
3 Parallel Computing Methodology in a Nutshell I
4 Parallel Computing Methodology in a Nutshell II
5 Potential in a Vacuum Filled Rectangular Box
6 Basic Sequential Algorithm
7 Update on the Grid
8 Parallelism is Straightforward
9 Communication is Needed
10 What is Parallel Architecture?
11 Parallel Computers -- Classic Overview
12 Distributed Memory Machines
13 Communication on Distributed Memory Architecture
14 Distributed Memory Machines -- Notes
15 Shared-Memory Machines
16 Communication on Shared Memory Architecture
17 Shared-Memory Machines -- Notes
18 Distributed Shared Memory Machines
19 Summary on Communication etc.
20 Communication Must be Reduced
21 Seismic Simulation of Los Angeles Basin
22 Irregular 2D Simulation -- Flow over an Airfoil
23 Heterogeneous Problems
24 Load Balancing Particle Dynamics
25 Reduce Communication
26 Minimize Load Imbalance
27 Parallel Irregular Finite Elements
28 Irregular Decomposition for Crack
29 Further Decomposition Strategies
30 Summary of Parallel Algorithms
31 Data Parallelism in Algorithms
32 Functional Parallelism in Algorithms
33 Pleasingly Parallel Algorithms
34 Parallel Languages
35 Data-Parallel Languages
36 Message-Passing Systems
37 Shared Memory Programming Model
38 Structure(Architecture) of Applications - I
39 Structure(Architecture) of Applications - II
40 Multi Server Model for metaproblems
41 Multi-Server Scenario
42 The 3 Roles of Java
43 Why is Java Worth Looking at?
44 What is Java Grande?
45 Java and Parallelism?
46 "Pure" Java Model For Parallelism
47 Pragmatic Computational Science January 2000 I
48 Pragmatic Computational Science January 2000 II

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