The keynote presentation by Dr. Larry Smarr at the Supercomputer '98 conference discusses the advances and future directions in supercomputing technology, architecture, and applications, highlighting the National Computational Science Alliance's role in driving computing capacity growth for scientific applications. It details the exponential increase in computational power required for simulations in various fields, such as molecular dynamics and cosmology, and the transition from vector to RISC processors in supercomputing. The presentation emphasizes the importance of collaborative efforts between academic and governmental research institutions to achieve breakthroughs in computational science.

1. National Computational Science Alliance
“Supercomputers: Directions in Technology,
Architecture, and Applications”
Keynote Presentation
Supercomputer ‘98
Mannheim, Germany
June 18, 1998
1
Dr. Larry Smarr
Director, National Computational Science Alliance and
the National Center for Supercomputing Applications
Professor in the Departments of Physics and Astronomy
University of Illinois Urbana-Champaign

2. National Computational Science Alliance
NCSA is the Leading Edge Site for the
National Computational Science Alliance
www.ncsa.uiuc.edu

3. National Computational Science Alliance
Scientific Applications Continue to Require
Exponential Growth in Capacity
MACHINE REQUIREMENT IN FLOPS
1010 1012
1014
1016
1018
1020
1995 NSF
Capability
108
2000 NSF
Leading Edge
Molecular Dynamics for
Biological Molecules
Computational
Cosmology
Turbulent
Convection
in Stars
Atomic/Diatomic
Interaction
QCD
1012
M
E
M
O
R
Y
B
Y
T
E
S
1010
108
1014
= Long Range Projections from Recent Applications Workshop
= Next Step Projections by NSF Grand Challenge Research Teams
= Recent Computations by NSF Grand Challenge Research Teams
ASCI in 2004
100 year climate
model in hours
NSF in 2004 (Projected)
From Bob Voigt, NSF

4. National Computational Science Alliance
The Promise of the Teraflop -
From Thunderstorm to National-Scale Simulation
Simulation by
Wilhelmson, et al.;
Figure from
Supercomputing and
the Transformation of
Science, Kaufmann
and Smarr, Freeman,
1993

5. National Computational Science Alliance
Accelerated Strategic Computing Initiative is
Coupling DOE Defense Labs to Universities
• Access to ASCI Leading Edge Supercomputers
• Academic Strategic Alliances Program
• Data and Visualization Corridors
http://www.llnl.gov/asci-alliances/centers.html

6. National Computational Science Alliance
Comparison of the DoE ASCI and the
NSF PACI Origin Array Scale Through FY99
www.lanl.gov/projects/asci/bluemtn
/Hardware/schedule.html
Los Alamos Origin System FY99
5-6000 processors
NCSA Proposed System FY99
6x128 and 4x64=1024 processors

7. National Computational Science Alliance
Future Upgrade Under Negotiation with NSF
NCSA Combines Shared Memory
Programming with Massive Parallelism
CM-5
CM-2

8. National Computational Science Alliance
The Exponential Growth of NCSA’s
SGI Shared Memory Supercomputers
1
10
100
1000
10000
Jan-94
Jan-95
Jan-96
Jan-97
Jan-98
Jan-99
Jan-00
Jan-01
SGI
Processors Doubling Every Nine Months!
Challenge
Power Challenge
Origin
SN1

9. National Computational Science Alliance
TOP500 Systems by Vendor
TOP500 Reports: http://www.netlib.org/benchmark/top500.html
CRI
SGI
IBM
Convex
HP
Sun
TMC
Intel
DEC
Japanese
Other
0
100
200
300
400
500 Jun-93
Nov-93
Jun-94
Nov-94
Jun-95
Nov-95
Jun-96
Nov-96
Jun-97
Nov-97
Jun-98
Number
of
Systems
Other
Japanese
DEC
Intel
TMC
Sun
HP
Convex
IBM
SGI
CRI

10. National Computational Science Alliance
Average User MFLOPS
Number
of
Users
0
50
100
150
20
40
60
80
100
120
140
160
180
200
220
240
260
280
300
March, 1992 - February, 1993
Average Performance, Users > 0.5 CPU Hour
Cray Y-MP4 / 64
Average Speed 70 MFLOPS
Peak Speed
MIPS R8000
Peak
Speed
Y-MP1
Why NCSA Switched From Vector to
RISC Processors
NCSA 1992 Supercomputing Community

11. National Computational Science Alliance
Replacement of Shared Memory Vector
Supercomputers by Microprocessor SMPs
TOP500 Reports: http://www.netlib.org/benchmark/top500.html
Top500
Installed
SC’s
0
100
200
300
400
500
Jun-93
Jun-94
Jun-95
Jun-96
Jun-97
Jun-98
MPP
SMP/DSM
PVP

12. National Computational Science Alliance
Top500 Shared Memory Systems
Vector Processors Microprocessors
TOP500 Reports: http://www.netlib.org/benchmark/top500.html
PVP Systems
0
100
200
300
Jun-93
Nov-93
Jun-94
Nov-94
Jun-95
Nov-95
Jun-96
Nov-96
Jun-97
Nov-97
Jun-98
Number
of
Systems
Europe
Japan
USA
SMP + DSM Systems
0
100
200
300
Jun-93
Nov-93
Jun-94
Nov-94
Jun-95
Nov-95
Jun-96
Nov-96
Jun-97
Nov-97
Jun-98
Number
of
Systems
USA

13. National Computational Science Alliance
Simulation of the Evolution of the Universe
on a Massively Parallel Supercomputer
12 Billion Light Years 4 Billion Light Years
Virgo Project - Evolving a Billion Pieces of Cold Dark Matter in a Hubble Volume -
688-processor CRAY T3E at Garching Computing Centre of the Max-Planck-Society
http://www.mpg.de/universe.htm

14. National Computational Science Alliance
Limitations of Uniform Grids for Complex
Scientific and Engineering Problems
Source: Greg Bryan, Mike Norman, NCSA
512x512x512 Run on 512-node CM-5
Gravitation Causes
Continuous
Increase in Density
Until There is a
Large Mass in a
Single Grid Zone

15. National Computational Science Alliance
Use of Shared Memory Adaptive Grids To
Achieve Dynamic Load Balancing
Source: Greg Bryan, Mike Norman, John Shalf, NCSA
64x64x64 Run with Seven Levels of Adaption on SGI Power Challenge,
Locally Equivalent to 8192x8192x8192 Resolution

16. National Computational Science Alliance
1
10
100
1000
10000
100000
1000000
1
16
31
46
61
76
91
106
121
136
151
166
181
Rank
CPU-Hours
Burned
100k to 1 M
10k to 100k
1k to 10k
100 to 1k
10 to 100
1 to 10
Extreme and Large PIs
Dominant Usage of NCSA Origin
January thru April, 1998

17. National Computational Science Alliance
Disciplines Using the NCSA Origin 2000
CPU-Hours in March 1995
Particle Physics
Chemistry
Materials Sciences
Engineering CFD
Astronomy
Physics
Industry
Molecular Biology
Other

18. National Computational Science Alliance
0
1
2
3
4
5
6
7 0
1
0
2
0
3
0
4
0
5
0
6
0
Processors
G
ig
a
flo
p
s
Origin-DSM
Origin-MPI
NT-MPI
SP2-MPI
T3E-MPI
SPP2000-DSM
Solving 2D Navier-Stokes Kernel -
Performance of Scalable Systems
Source: Danesh Tafti, NCSA
Preconditioned Conjugate Gradient Method With
Multi-level Additive Schwarz Richardson Pre-conditioner
(2D 1024x1024)

19. National Computational Science Alliance
A Variety of Discipline Codes -
Single Processor Performance Origin vs. T3E
0
20
40
60
80
100
120
140
160
Origin T3E
Single
Processor
MFLOPS
QMC
RIEMANN
Laplace
QCD
PPM
PIMC
ZEUS

20. National Computational Science Alliance
Alliance PACS Origin2000 Repository
http://scv.bu.edu/SCV/Origin2000/
Kadin Tseng, BU, Gary Jensen, NCSA, Chuck Swanson, SGI
John Connolly, U Kentucky Developing Repository for HP Exemplar

21. National Computational Science Alliance
• NEC SX-5
– 32 x 16 vector processor SMP
– 512 Processors
– 8 Gigaflop Peak Processor
• IBM SP
– 256 x 16 RISC Processor SMP
– 4096 Processors
– 1 Gigaflop Peak Processor
• SGI Origin Follow-on
– 32 x 128 RISC Processor DSM
– 4096 Processors
– 1 Gigaflop Peak Processor
High-End Architecture 2000-
Scalable Clusters of Shared Memory Modules
Each is 4 Teraflops Peak

22. National Computational Science Alliance
Emerging Portable Computing Standards
• HPF
• MPI
• OpenMP
• Hybrids of MPI and OpenMP

23. National Computational Science Alliance
Basket of Applications Average Performance
as Percentage of Linpack Performance
0
200
400
600
800
1000
1200
1400
1600
1800
T90 C90 SPP-
2000
SP2-
160
Origin
195
PCA
Linpack
Apps. Ave.
22%
25%
14% 19%
33% 26%
Applications Codes:
CFD
Biomolecular
Chemistry
Materials
QCD

24. National Computational Science Alliance
Harnessing Distributed UNIX Workstations -
University of Wisconsin Condor Pool
Condor Cycles
CondorView, Courtesy of Miron Livny, Todd Tannenbaum(UWisc)

25. National Computational Science Alliance
NT Workstation Shipments
Rapidly Surpassing UNIX
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1995 1996 1997
Workstations
Shipped
(Millions)
UNIX
NT
Source: IDC, Wall Street Journal, 3/6/98

26. National Computational Science Alliance
First Scaling Testing of ZEUS-MP on
CRAY T3E and Origin vs. NT Supercluster
“Supercomputer performance at mail-order prices”-- Jim Gray, Microsoft
access.ncsa.uiuc.edu/CoverStories/SuperCluster/super.html
Zeus-MP Hydro Code
Running Under MPI
• Alliance Cosmology Team
• Andrew Chien, UIUC
• Rob Pennington, NCSA
0
2
0
4
0
6
0
8
0
1
0
0
1
2
0
1
4
0
T
3
E
O
r
i
g
i
n
N
T
S
i
n
g
l
e
P
r
o
c
e
s
s
o
r
S
p
e
e
d
o
n
Z
E
U
S
-
M
P
(
M
F
L
O
P
S
)
0
1
2
3
4
5
6
7
8
0
2
0
4
0
6
0
8
0
1
0
0
1
2
0
1
4
0
1
6
0
1
8
0
2
0
0
P
r
o
c
e
s
s
o
r
s
G
F
L
O
P
S
T
3
E
O
r
i
g
i
n
N
T
/
I
n
t
e
l

27. National Computational Science Alliance
NCSA NT Supercluster
Solving Navier-Stokes Kernel
Preconditioned Conjugate Gradient Method With
Multi-level Additive Schwarz Richardson Pre-conditioner
(2D 1024x1024)
Single Processor Performance:
MIPS R10k 117 MFLOPS
Intel Pentium II 80 MFLOPS
Danesh Tafti, Rob Pennington, Andrew Chien NCSA
0
10
20
30
40
50
60
0
10
20
30
40
50
60
Processors
Speedup
NT MPI
Origin MPI
Origin SM
Perfect
0
1
2
3
4
5
6
7
0
10
20
30
40
50
60
70
Processors
Gigaflops
NT MPI
Origin MPI
Origin SM

28. National Computational Science Alliance
Near Perfect Scaling of Cactus -
3D Dynamic Solver for the Einstein GR Equations
0
20
40
60
80
100
120
0
20
40
60
80
100
120
Processors
Scaling
Origin
NT SC
Ratio of GFLOPs
Origin = 2.5x NT SC
Danesh Tafti, Rob Pennington, Andrew Chien NCSA
Cactus was
Developed by
Paul Walker,
MPI-Potsdam
UIUC, NCSA

29. National Computational Science Alliance
NCSA Symbio - A Distributed Object Framework
Bringing Scalable Computing to NT Desktops
http://access.ncsa.uiuc.edu/Features/Symbio/Symbio.html
• Parallel Computing on NT Clusters
– Briand Sanderson, NCSA
– Microsoft Co-Funds Development
• Features
– Based on Microsoft DCOM
– Batch or Interactive Modes
– Application Development Wizards
• Current Status & Future Plans
– Symbio Developer Preview 2 Released
– Princeton University Testbed

30. National Computational Science Alliance
The Road to Merced
http://developer.intel.com/solutions/archive/issue5/focus.htm#FOUR