1
Who needs a supercomputer?
Professor Allan Snavely
Professor Snavely, University of California
University of California, San Diego
and
San Diego Supercomputer Center
SAN DIEGO SUPERCOMPUTER CENTER
UCSD
Aren’t computers fast enough already?
 This talk argues computer’s are not fast enough
already
 Nor do supercomputers just naturally get faster as a result
of Moore’s Law. We explore implications of:
 Moore’s Law
 Amdahl’s Law
 Einstein’s Law
 Supercomputers are of strategic importance, enabling a
“Third Way” of doing science-by-simulation

Example: Terashake Earthquake simulation
 Viable National Cyberinfrastructure requires centralized
supercomputers
 Supercomputing in Japan, Europe, India, China
 Why SETI@home + Moore’s Law does not solve all our problems
PMaC
Performance Modeling and Characterization Lab
San Diego Supercomputer Center
The basic components of a computer
 Your laptop has these:
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Performance Modeling and Characterization Lab
San Diego Supercomputer Center
Supercomputers (citius, altius , fortius)
 Supercomputers are just “faster, higher, stronger”,
than your laptop, more and faster processors etc.
capable of solving large scientific calculations
PMaC
Performance Modeling and Characterization Lab
San Diego Supercomputer Center
An army of ants approach
 In Supercomputers such as Blue Gene, DataStar,
thousands of CPUs cooperate to solve scientific
calculations
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Performance Modeling and Characterization Lab
San Diego Supercomputer Center
Computers live a billion seconds to our every
one!
Definitions:
Latency is distance measured in time
Bandwidth is volume per unit of time
Thus, in their own sense of time, the
latencies and bandwdiths across the
machine room span 11 orders of
magnitude! (from Nanoseconds to
Minutes.) To a supercomputer, getting
data from disk is like sending a rocketship to Saturn!
PMaC
Performance Modeling and Characterization Lab
San Diego Supercomputer Center
Moore’s Law
 Gordon Moore (co-founder of Intel) predicted in 1965 that the
transistor density of semiconductor chips would double roughly
every 18 months.
 Moore’s law has had a decidedly mixed impact, creating new
opportunities to tap into exponentially increasing computing
power while raising fundamental challenges as to how to harness
it effectively.
 Things Moore never said:



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“computers double in speed every 18 months” 
“cost of computing is halved every 18 months” 
“cpu utilization is halved every 18 months” 
Performance Modeling and Characterization Lab
San Diego Supercomputer Center
Moore’s Law
100,000,000
10,000,000
Transistors
R10000
Pentium
1,000,000
i80386
i80286
100,000
R3000
R2000
i8086
10,000
i8080
i4004
1,000
1970 1975
1980 1985 1990 1995
2000 2005
Year
Moore’s Law: the number of transistors per processor chip by doubles every 18 months.
PMaC
Performance Modeling and Characterization Lab
San Diego Supercomputer Center
Snavely’s Top500 Laptop?
 Among other startling implications of Moore’s Law is the fact that
the peak performance of the typical laptop would have placed it
as one of the 500 fastest computers in the world as recently as
1995.
 Shouldn’t I just go find another job now?
 No, because Moore’s Law has several more subtle implications
and these have raised a series of challenges to utilizing the
apparently ever-increasing availability of compute power; these
implications must be understood to see where we are today in
High Performance superComputing (HPC).
PMaC
Performance Modeling and Characterization Lab
San Diego Supercomputer Center
The Vonn Neumann bottleneck
 Scientific calculations involve operations upon large
amounts of data, and it is in moving data around
within the computer that the trouble begins. As a very
simple pedagogical example consider the expression
A+B=C
 The computer has to load A and B, “+” them together,
and store C
 “+” is fast by Moore’s Law, load and store is slow by
Einstein’s Law
PMaC
Performance Modeling and Characterization Lab
San Diego Supercomputer Center
Supercomputer “Red Shift”
 While the absolute speed of all computer
subcomponents have been changing rapidly, they
have not all been changing at the same rate.
 While CPUs get faster they spend more time sitting
around waiting for data
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Performance Modeling and Characterization Lab
San Diego Supercomputer Center
Amdahl’s Law
 The law of diminishing returns
 When a task has multiple parts, after you speed up one part
a lot, the other parts come to dominate the total time
 An example from cycling:
 On a hilly closed-loop course you cannot ever average more
than 2x your uphill speed even if you go downhill at the speed
of light!
 For supercomputers this means even though processors
get faster the overall time to solution is limited by memory
and interconnect speeds (moving the data around)
PMaC
Performance Modeling and Characterization Lab
San Diego Supercomputer Center
Red Shift and the Red Queen
 It takes all the running you can do, to keep in the same
place. If you want to get somewhere else, you must run
at least twice as fast as that!
 Corollary: Allan’s laptop is not a balanced system!
 System utilization is cut in half every 18 months?
 Fundamental R&D in latency hiding, high bandwidth
network, Computer Architecture
PMaC
Performance Modeling and Characterization Lab
San Diego Supercomputer Center
3 ways of science
 Experiment
 Theory
 Simulation
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Performance Modeling and Characterization Lab
San Diego Supercomputer Center
How Dangerous is the Southern San Andreas Fault?




The SCEC TeraShake
simulation is a result of
immense effort from the
Geoscience community
for over 10 years
Focus is on understanding
big earthquakes and how
they will impact sedimentfilled basins.
Simulation combines
massive amounts of data,
high-resolution models,
large-scale supercomputer
runs
Major Earthquakes
on the San
Andreas Fault,
1680-present
1906
M 7.8
1857
M 7.8

1680
M 7.7
?
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TeraShake results provide
new information enabling
better

Estimation of
seismic risk

Emergency preparation,
response and planning

Design of next
generation of
earthquake-resistant
structures
Such simulations provide
potentially immense
benefits in saving both
many lives and billions in
economic losses
Performance Modeling and Characterization Lab
San Diego Supercomputer Center
TeraShake Animation
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Performance Modeling and Characterization Lab
San Diego Supercomputer Center
SDSC and Data Intensive Computing
Data (more BYTES)
Data-oriented Science and
Engineering Environment
TeraShake
Brain
mapping
Home, Lab,
Campus,
Desktop
Traditional
HPC
environment
Compute (more FLOPS)
PMaC
Performance Modeling and Characterization Lab
San Diego Supercomputer Center
The Japanese Earth Simulator
 Took U.S. HPC Community by surprise in 2002 – “Computenik”
 For 2 years had more flops capacity than top 5 U.S. systems
 Approach based on specialized HPC design
 Still has more data moving capacity
 Sparked “space race” in HPC, Blue Gene surpassed for flops
2005
PMaC
Performance Modeling and Characterization Lab
San Diego Supercomputer Center
Summary
 “Red Shift” means the promise implied by Moore’s
Law is largely unrealized for scientific simulation that
by necessity operate on large data
 Consider “The Butterfly Effect”
 Supercomputer Architecture is a hot field
 Challenges from Japan, Europe, India, China
 Large centralized, specialized compute engines are a
vital national strategic resources
 Grids, utility programing, SETI@home etc. do not meet
all the needs of largescale scientific simulation for
reason that should now be obvious
 Consider a galactic scale
PMaC
Performance Modeling and Characterization Lab
San Diego Supercomputer Center