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CPS615-End of Numerical Integration and Very End of HPF

Given by Geoffrey C. Fox at Delivered Lectures of CPS615 Basic Simulation Track for Computational Science on 24 October 96. Foils prepared 11 November 1996

This covers two topics:
Monte Carlo Integration for large scale Problems using Experimental and Theoretical high energy physics as an example
This includes accept-reject methods, uniform weighting and parallel algorithms
Then we complete HPF discussion with embarassingly parallel DO INDEPENDENT discussed in Monte Carlo case
And HPF2 Changes

This mixed presentation uses parts of the following base foilsets which can also be looked at on their own!
Master Set of Foils for 1996 Session of CPS615
CPS615 Numerical Integration Module
Overview of Fortran 90 and HPF Fall 96

Table of Contents for CPS615-End of Numerical Integration and Very End of HPF

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CPS 615 Lectures 1996 Fall Semester -- October 24
1 Delivered Lectures for CPS615 -- Base Course for the Simulation Track of Computational Science
Fall Semester 1996 --
Lecture of October 24 - 1996
2 Abstract of Oct 24 1996 CPS615 Lecture
Last Part of Numerical Integration Discussion
3 51:Accept/Reject Method for Generating General Probability Distributions
4 52:Estimate of Maximum in Accept/Reject Method
5 53:Introduction to Metropolis Method
6 54:The Metropolis Procedure
7 55:Why Metropolis Method Works
8 56:Monte Carlo Examples Example 1: An Experimental Physics Application
9 57:A High Energy Experiment Scenario
10 58:An Experimental Physics Monte Carlo
11 59:Double Monte Carlo's Again --- I
12 60:Double Monte Carlo's Again --- II
13 61:A Monte Carlo Event
14 62:Uniform Weight Events
15 64:Example 2: Parallel Computing for ``Event'' Monte Carlos
16 65:Example 3: Lattice Monte Carlo Theoretical Physics
17 66:Choice of Points in Lattice Monte Carlo
18 67:Pictorial View of Lattice Monte Carlo Integrands
19 68:Metropolis and Heat Bath Methods
20 69:Calculation of Observables
21 70:Example 4: Parallel Computing for Lattice Theory
22 71:A Problem Lattice Decomposed Onto a 64-node Machine Arranged as a Machine Lattice
Very last Part of HPF Discussion
23 !HPF$ INDEPENDENT, NEW Variable
24 Extrinsics in HPF
25 High Performance Fortran HPF2 Changes
26 ON HOME for Computation Placement
27 Reductions in INDEPENDENT DO Loops
28 Spawning Tasks in HPF
29 New Data Mapping Features in HPF 2.0 - I
30 New Data Mapping Features in HPF 2.0 - II
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