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Master Foilset for CPS615 Introduction -- Material from Culler and Koelbel

Given by Geoffrey C. Fox, Nancy McCracken at Computational Science for Simulations on Fall Semester 1998. Foils prepared 24 August 98

We Introduce Computational Science and Driving Forces
  • Technology Advances and Commodity Trends
  • Inevitability of Parallelism
  • Integration of Distributed and Parallel Computing
  • Comparison with Internetics
We give a simple overview of parallel architectures today with distributed, shared or distributed shared memory
We describe the growing importance of Java
We explain pragmatic choices
  • MPI with Fortran and C today
  • Java Grande is future?

Table of Contents for Master Foilset for CPS615 Introduction -- Material from Culler and Koelbel

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1 Framework for Computational Science
2 Abstract of Computational Science Presentation
3 What is Computational Science ?
4 Synergy of Parallel Computing and Web Internetics as Unifying Principle
5 Basic CPS615 Contact Points
6 Course Organization
7 Material Covered in this Course
8 Structure of CPS615 - II
9 What are Parallel and Distributed Computing?
10 Why Parallel Computing?
11 Parallel Computing Technology Rationale
12 Motivating Applications
13 Some Comments on Simulation and HPCC
14 The Multicomputer: an Idealized Parallel Computer
15 Multicomputer Architecture
16 Multicomputer Cost Model
17 Sequential Memory Structure
18 Parallel Computer Memory Structure
19 Real Parallel Computers Architectures
20 Parallel Computers -- Classic Overview
21 Distributed Memory MIMD Multiprocessor
22 Distributed Memory Machines
23 Distributed Memory Machines -- Notes
24 Shared Memory MIMD Multiprocessor
25 Shared-Memory Machines
26 Shared-Memory Machines -- Notes
27 Distributed Shared Memory (DSM)
28 Distributed Shared Memory Machines
29 Workstation Clusters
30 Parallel Algorithms
31 Data Parallelism in Algorithms
32 Some Illustrative Examples of Parallel Applications!
33 Functional Parallelism in Algorithms
34 Structure(Architecture) of Applications - I
35 Structure(Architecture) of Applications - II
36 Multi Server Model for metaproblems
37 Multi-Server Gateway Tier
38 Pleasingly Parallel Algorithms
39 Parallel Languages
40 Data-Parallel Languages
41 Message-Passing Systems
42 A Simple Parallel Programming Model
43 Properties of Programming Model
44 Some Steps in Parallel Programming
45 Partitioning
46 Communication
47 Agglomeration
48 Mapping
49 Example: Atmosphere Model
50 Atmosphere Model: Numerical Methods
51 Atmosphere Model: Partition
52 Atmosphere Model: Communication
53 Atmosphere Model: Agglomeration
54 Atmosphere Model: Mapping
55 What is Parallel Architecture?
56 Why Study Parallel Architecture as a computer scientist?
57 Why Study Architecture Today?
58 Inevitability of Parallel Computing
59 Application Trends
60 TPC-C (database transaction processing)
61 Summary of Application Trends
62 Technology Trends -- CPU's
63 General Technology Trends
64 Technology: A Closer Look
65 Clock Frequency Growth Rate
66 Transistor Count Growth Rate
67 Similar Story for Storage
68 The HPCC Dilemma and its Solution
69 What is Commodity Software
70 The Computing Pyramid
71 Implications of the Computing Pyramid
72 The 3 Roles of Java
73 Why is Java Worth Looking at?
74 What is Java Grande?
75 Java and Parallelism?
76 "Pure" Java Model For Parallelism
77 Pragmatic Computational Science August 1998
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