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Overview of HPC for Physical Sciences
Given by
Geoffrey C. Fox
at Mardi Gras Conference on Concurrent Computing in Physical Sciences on
February 18, 1993
.
Foils prepared
October 22 1997
This overviews status of HPCC architectures
Software approaches focussing on HPF and an Application Analysis
Problem Architectures Load Balancing and the Complex System Approach
Table of Contents for Overview of HPC for Physical Sciences
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1
Overview of High Performance Computing for Physical Sciences
2
Performance of Computers as a Function of Time
3
Performance of QCD Machines
4
When will Parallel Computing Take Over ?
5
Parallelism Implies
6
Program in Computational Science Implemented within current academic framework
7
We have learnt that Parallel Computing Works !
8
METHODOLOGY
9
Sideways View of Concurrent Computing Mappings
10
Sample uses of Concurrent Computers
- 4 Nodes
11
Parallel Computing Trends to Year 2000
12
39 National Grand Challenges
13
39 National Grand Challenges (II)
14
39 National Grand Challenges (III)
15
39 National Grand Challenges (IV)
16
Most Grand Challenges are
17
ACTION Motivation
18
Applications of Interest to Industry IA
19
Applications of Interest to Industry IB
20
Applications of Interest to Industry IC
21
Pluses and Minuses of Parallel Computing
22
P C E T E C H Ñ A Result of
23
The Life History of an HPC Idea
24
Core Enabling Software Technologies
25
Core Enabling Algorithms and Components
26
Portable Scalable Languages
27
Problem Architectures
28
Software Problem Architecture Interactions
29
Why build on existing languages - especially Fortran / C
30
Fortran( C ) Plus Message Passing
31
Fortran( C ) Plus Message Passing
32
Data Parallel Fortran
33
Data Parallel Fortran ( C, C++, LISP, ADA )
34
The Origins of High Performance Fortran
35
Strategy for HPF
36
Model for Scalable Languages
37
Dynamically Triangulated Random Surfaces
38
Update Strategies for DTRS
39
N=36 Wireframe DTRS
40
N=144 Lambda =1.5 Colored DTRS
41
N=144 Lambda=1 Colored DTRS
42
Computational Issues and Code Performance Optimization
43
Sequential Computer Architecture
44
Performance of Random Surface Code
45
Parallel Algorithms
46
Parallel Grid Generation
47
What is Fortran 90?
48
HPF Language Features - 1
49
HPF Language Features - 2
50
FORTRAN-90D
The First Implementation of HPF
(NPAC, Syracuse University)
Current Status
51
Fortran90D Performance on Gaussian Elimination
52
Gaussian Elimination
Example of Fortran90D Source Code
53
Fortran90D Interface
54
HPF Directives
55
Data Alignment
56
Data Distribution
57
FORALL
58
DO INDEPENDENT
59
HPF Library
60
Intrinsic Library
61
HPF Library
62
Fortran 90 Local Routine Intrinsics
63
Does HPF need a different type of compiler ?
64
HPF Interpreter
65
Benchmarking Set ( Fortran90D and Fortran 77 )
66
HPF/FORTRAN-90D Benchmark Suite
67
The final draft of the HPF Language Specification is version 1.0 - DRAFT, dated January 25, 1993
68
Request for Public Comment on High Performance Fortran
69
Application Structure Versus Fortran90D Features
70
What applications does HPF support?
71
Current HPF can do I .....
72
Current HPF can do II.....
73
HPF can express using FORALL
74
Classic Irregular Mesh Application
75
HPF Can Express
76
Simulation of Spin Models of Magnets
77
New Monte Carlo Algorithms
78
Magnetization for Random Field Ising Model -- Metropolis
79
Magnetization for Random Field Ising Model -- Simulated Annealing
80
Wolff cluster (bands shown in yellow) for 3 state Potts model at Tc
81
Swendsen-Wang clusters (boundaries shown in black) for 3 state Potts model at Tc
82
Cluster Algorithm versus Metropolis
83
Parallel Algorithms
84
Parallel Cluster Algorithms
85
MIMD algorithm on nCUBE-1
86
SIMD algorithms on CM-2
87
Autocorrelation Plots for Cluster Algorithms
88
HPF probably cannot express well
89
I do not know how to express - let alone optimize -
90
Late breaking results
91
Large N-Body Calculations (Quinn, Salmon, Warren)
92
Hierarchical Decomposition
93
Ncube Speed Up of Barnes Hut Algorithm
94
17x106 Body Simulation
Diameter 250Mpc
Quinn, Salmon, Warren, Zurek
95
The largest "galaxy" halo (137,000 bodies) from the 8.8M body simulation
(Warren, Fullagar, Quinn, Zurek)
96
8M bodies - 10 Mpc diameter
Final state with ~700 resolved "galaxies"
(Warren, Quinn, Zurek)
97
Smooth Particle Hydro simulation of the collision of two "main sequence stars." 137,000 bodies (Warren,Davies)
98
Expressing Problem Structure in Language
99
The map of Problem ---> Computer is performed in two or more stages
100
From Problem to Machine Space as a Mapping
101
Different Granularities of Decomposition I
102
Different Granularities of Decomposition II
103
Compiler/Interpreter Tradeoffs at Different Levels of Granularity
104
The Mapping of Heterogeneous MetaProblems onto Heterogeneous MetaComputer Systems
105
Mapping of Irregular Grid
106
Finding General Maps for FortranD/HPF
107
Three Physical Optimization Methods for Allocating Data to Multicomputer Nodes
108
Finite Element Mesh
109
Graph Contraction
110
Some Results of Load Balancing Studies I
111
Some Results of Load Balancing Studies II
112
Physics Analogy for Load Balancing
113
Complex System SHLSoft governed by Hamiltonian = Execution Time
114
PHYSICS ANALOGY FOR STATIC AND DYNAMIC LOAD BALANCING
115
Definition of Temperature for a Complex System
116
Particle dynamics problem on a four node system
117
Energy Structure in Physics Analogy with Multiple Minima
118
Phase Transitions in Physical model -- Scattered versus Domain Decompositions
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