United States General Accounting Office
____________________________________________________________________________
GAO Report to Congressional Requesters
____________________________________________________________________________
July 1991 HIGH-PERFORMANCE
COMPUTING
Industry Uses of
Supercomputers and
High-Speed Networks
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GAO/IMTEC-91-58
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i
_____________________________________________________________________________
GAO United States
General Accounting Office
Washington, D.C. 20548
______________________________________________________
Information Management and
Technology Division
B-244488
July 30, 1991
The Honorable Ernest F. Hollings
Chairman, Senate Committee on Commerce,
Science, and Transportation
The Honorable Al Gore
Chairman, Subcommittee on Science,
Technology, and Space
Senate Committee on Commerce, Science,
and Transportation
The Honorable George E. Brown, Jr.
Chairman, House Committee on Science,
Space, and Technology
The Honorable Robert S. Walker
Ranking Minority Member
House Committee on Science, Space,
and Technology
The Honorable Tim Valentine
Chairman, Subcommittee on Technology
and Competitiveness
House Committee on Science, Space,
and Technology
The Honorable Tom Lewis
Ranking Minority Member
Subcommittee on Technology
and Competitiveness
House Committee on Science, Space,
and Technology
This report responds to your October 2, 1990, and
March 11, 1991, requests for information on
supercomputers and high-speed networks. You
specifically asked that we
- provide examples of how various industries are using
supercomputers to improve products, reduce costs, save
time, and provide other benefits;
- identify barriers preventing the increased use of
supercomputers; and
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- provide examples of how certain industries are using
and benefitting from high-speed networks.
As agreed with the Senate Committee on Commerce,
Science, and Transportation, and Subcommittee on
Science, Technology, and Space, our review of
supercomputers examined five industries--oil,
aerospace, automobile, and chemical and
pharmaceutical. These industries are known for using
supercomputers to solve complex problems for which
solutions might otherwise be unattainable. Appendixes
II through V provide detailed accounts--drawn from 24
companies contacted within these industries--of how
supercomputers are used to improve products and
provide other benefits. We also obtained information
from 10 companies in the oil, automobile, and computer
industries concerning how they are using and
benefitting from high-speed computer networks. We did
not verify the accuracy of the examples of benefits
provided by the various companies. Appendixes I, VI,
and VII, respectively, provide additional information
on the objectives, scope, and methodology of our
review, and identify the companies examined to assess
uses of supercomputers and high-speed networks.
#####################________________________________________________________
RESULTS IN BRIEF Supercomputers contribute significantly to the oil,
automobile, aerospace, and chemical and
pharmaceutical industries' ability to solve complex
problems. They enable companies within these
industries to design new and better products in less
time, and to simulate product tests that would have
been impossible without spending months developing and
experimenting with expensive product models. Some
companies have attributed significant cost savings to
the use of supercomputers. For example, although
exact figures were not always available,
representatives of some automobile and aerospace
companies estimated that millions of dollars have been
saved on specific models or vehicle parts because of
reduced manufacturing or testing costs. In addition,
one oil company representative estimated that over the
last 10 years, supercomputer use has resulted in
increased production of oil worth between $5 billion
and $10 billion from two of the largest U.S. oil
fields.
Despite widespread use of supercomputers for certain
applications, representatives of these companies told
us that several key barriers currently hinder their
greater use. These barriers include (1) the high cost
of supercomputers, (2) a lack of application
software, (3) the cultural resistance to the shift
from physical experiments to an increased reliance on
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computational experiments, and (4) a lack of
supercomputing education and training.
High-speed networks contribute to improved
productivity by enabling industries to more
efficiently share information and resources and
collaborate on product development over distances.
Companies within the oil, automobile, and computer
industries, for example, rely on high-speed networks
to transfer large graphics and data files, and access
computers worldwide. In many cases these companies
must use high-speed networks (as opposed to those
operating at lower speeds) because (1) the
applications in use require high transmission speeds,
for example to provide instant images for interactive
videoconferencing, (2) high volumes of traffic in one
or more applications are being transmitted, or (3)
fast response is needed for such applications as data
base queries. Several companies reported that they
would not be able to develop products in a timely
manner without high-speed networks.
#####################________________________________________________________
BACKGROUND A supercomputer, by its most basic definition, is the
most powerful computer available at a given time.
Current supercomputers, costing from about $1 million
to $30 million, are capable of performing billions of
calculations each second. Computations requiring
hours or days on conventional computers may be
accomplished in a few minutes or seconds on a
supercomputer.
Although the term supercomputer does not refer to a
particular design or type of computer, supercomputers
generally use vector or parallel processing. With
vector processing, a supercomputer lines up billions
of calculations and then uses one or several large
processors to perform these calculations. In parallel
processing, many smaller processors work on multiple
parts of a program concurrently. The trend in
supercomputer design is to add more processors to
achieve greater performance. Massively parallel
supercomputers consisting of between 1,000 and 64,000
processors now exist.
The unique computational power of supercomputers
makes it possible to solve critical scientific and
engineering problems that cannot be dealt with
satisfactorily by theoretical, analytical, or
experimental means. Scientists and engineers in many
fields--including aerospace, petroleum exploration,
automobile design and testing, chemistry, materials
science, and electronics--emphasize the value of
supercomputers in solving complex problems. Much of
this work involves the use of workstations for
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scientific visualization--a technique allowing
researchers to convert masses of data into three-
dimensional images of objects or systems under study.
These images enable researchers to comprehend more
readily what data reveal and facilitate the
understanding of problems by different types of
scientists and engineers.
While supercomputers are still relatively limited in
use, the number of supercomputers has risen
dramatically in the last decade. In the early 1980s,
most of the 20 to 30 supercomputers in existence were
operated by government agencies for such purposes as
weapons research and weather modeling. Today, about
280 supercomputers#1 are in use worldwide. The
Government (including defense-related industry)
remains the largest user, although private industry
has been the fastest growing user segment for the past
few years, and is projected to remain so.
A high-speed network is generally defined as a
network operating at speeds of T1--1.544 million bits
per second--or higher. Prior to 1977, high-speed
networks were employed exclusively by the telephone
companies. By the early 1980s, however, these
services had become widely available to commercial
customers.
Today, thousands of high-speed networks exist, fueled
by demands for a variety of applications, such as
electronic mail, data file transfer, and distributed
data base access. Networks operating at T1-speeds are
common and provide sufficient capability to meet most
application needs. However, there is a growing demand
for higher-speed networks, such as those operating at
T3-speeds (45 million bits per second) or greater, to
transmit multiple low-speed applications to many users
at the same time. In addition, many industries now
look to such networks as a means of transmitting more
advanced applications that result from the use of
supercomputers and other sophisticated technologies.
The growth of T1 and T3 lines is expected to be great,
according to Northern Business Information/Datapro, a
research company and industry analyst, which projected
that revenues for T1 and T3 will increase three-fold
between 1990 and 1994.
______________________________________________________
1 This figure includes only high-end
supercomputers such as those manufactured by Cray
Research, Inc. Including International Business
Machines (IBM) mainframes with vector facilities would
about double this number.
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#####################________________________________________________________
INDUSTRIES BENEFIT Supercomputers provide the five selected
FROM SUPERCOMPUTING industries with the ability to develop new and better
products more quickly. Although most companies within
these industries could not provide precise figures to
quantify the extent of gains realized, nearly all
believed that supercomputers have enabled them to
perform previously impossible tasks, or achieve
significant cost reductions or time savings.
Moreover, industry representatives believed that
greater benefits would be realized in the future, as
these companies move toward using more powerful
supercomputers with thousands of processors. Of the
21 companies that commented on the issue, 19 said that
they will be using massively parallel supercomputers
to a greater extent in the future.#2 Details on each
industry's use of supercomputers are in appendixes II
through V.
_____________________________________________________________________________
The Oil Industry As an early user of supercomputers, the oil industry
has realized substantial benefits from supercomputer
applications. By using two key applications for
processing seismic data#3 and simulating reservoirs,
oil companies have improved their ability to determine
the location of reservoirs and to maximize recovery of
oil and gas from those reservoirs. This ability has
become increasingly important because of the low
probability of discovering large oil fields in the
continental U.S. New oil fields are often small and
located in harsh environments, making exploration and
production difficult. Several industry
representatives estimated that the use of
supercomputers reduces the number of dry wells drilled
(at a cost of $.5 million to over $50 million per
well) by about 10 percent. In addition, an Atlantic
Richfield Company (ARCO) representative estimated that
supercomputer use has led to increased oil production
worth billions of dollars at two large fields.
_____________________________________________________________________________
The Aerospace Engineers and researchers in the aerospace industry
Industry have used supercomputers since the early 1980s to
design, develop, and test aerospace vehicles and
related components. Supercomputers, for example, have
enabled engineers to analyze aircraft structural
composition for design flaws and to simulate their
______________________________________________________
2 Three out of 24 representatives did not
comment on the issue for proprietary reasons.
3 Seismic data reveal characteristics about the
earth and are gathered using sound recording devices
to measure the speed that vibrations travel through
the earth.
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performance in wind tunnels. This ability is
important because wind tunnels are expensive to build
and maintain, and cannot reliably detect certain
airflow phenomena. Simulation permits a reduction in
physical model testing, and substantial savings in
time and money. As a major user of supercomputers,
McDonnell Douglas estimates that supercomputer
simulations saved about a year in the design and
testing of its new C-17 military aircraft.
_____________________________________________________________________________
The Automobile Since 1984, automobile manufacturers have
Industry increasingly relied on supercomputers to design
vehicles that are safer, lighter, more economical, and
better built. By the late 1980s, the world's 12
largest automobile companies had acquired
supercomputers. A primary supercomputer application--
crash analysis--is used to simulate how vehicle
structures collapse on impact and how fast passengers
move forward. These simulations provide more precise
engineering information than was possible from
physically crashing pre-prototype vehicles. They also
reduce the number of vehicles required for these tests
by about 20 to 30 percent. Consequently, companies
have been able to save millions of dollars annually.
According to General Motors Corporation
representatives, for example, supercomputers enabled
the company to crash 100 fewer vehicles when
developing some of its 1992 models, than it did in
1987. Each test vehicle costs from $50,000 to
$750,000, depending on whether a production vehicle or
prototype is used.
_____________________________________________________________________________
The Chemical and Supercomputers also play a growing role in the
Pharmaceutical chemical and pharmaceutical industries,
Industries although their use is still in its infancy.
From computer-assisted molecular design to synthetic
materials research, these companies increasingly rely
on supercomputers to study critical design parameters
and more quickly and accurately interpret and refine
experimental results. Industry representatives told
us that the use of supercomputers will result in new
discoveries that otherwise may not have been
possible. Du Pont, for example, is developing
replacements for chlorofluorocarbons, compounds used
as coolants for air conditioners, that are thought to
contribute to the depletion of ozone in the
atmosphere. In designing a new process to produce
substitute compounds, Du Pont is using a supercomputer
to make certain calculations needed for this process.
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These calculations, on a supercomputer, require a few
days at a cost of between $2,000 to $5,000.
Previously, however, such tests cost about $50,000 and
required up to 3 months to conduct.
#####################________________________________________________________
BARRIERS IMPEDE Although supercomputers have yielded highly
GREATER USE OF visible contributions in the selected
SUPERCOMPUTERS industries, representatives told us that many
aspects of supercomputer use remain untapped, because
of the following significant barriers.
High cost: Currently, supercomputers cost between $1
million and $30 million, not including the cost of
software development, maintenance, or trained staff.
Lack of software: While the evolution of software for
vector supercomputers has accelerated over the past
decade, little reliable software has been developed
for parallel supercomputers. This is in part due to
the lack of software tools for developing new
parallel software and converting vector software so
that it can be used on massively parallel
supercomputers.
Cultural resistance: Many companies or industries,
particularly the chemical and pharmaceutical
industries, rely more heavily on physical
experimentation than necessary, according to
representatives. Many scientists and managers see the
use of computational science as a dramatic break with
past practice, and such a major shift in research
methodology is difficult to accept.
Lack of supercomputer training and education: Before
1985, university students and professors performed
little of their research on supercomputers. Thus, for
many years industry hired students from universities
who did not bring supercomputing skills and experience
to their jobs. According to Du Pont and Eli Lilly
representatives, universities are still not providing
a sufficient number of students skilled in the use of
supercomputers. A Ford Motor Company representative
also noted that there is a scarcity of trained staff
in computational fluid dynamics, an important
application to the automobile industry. Currently,
formal supercomputer education is primarily limited to
the National Science Foundation (NSF) university
supercomputer centers.
#####################________________________________________________________
INDUSTRY USES OF Like supercomputers, high-speed networks are
HIGH-SPEED NETWORKS making valuable contributions to many industries.
Companies in the oil, automobile, and computer
industries, for example, increasingly rely on high-
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speed networks to share resources and provide various
types of person-to-person communications. Many oil
company representatives, in particular, reported
network traffic increases, ranging from 10 to more
than 100-fold over the past 5 years. Many companies
thought that significant benefits--including monetary
savings, reduced time-to-market, and improved product
quality--have resulted from their use of high-speed
networks.
The companies we contacted primarily use high-speed
networks operating at T1-speeds (1.544 million bits
per second). A significantly smaller, although
growing, number of companies also use higher-speed T3
networks of 45 million bits per second. These
networks generally consist of private lines, leased
exclusively for each company's use, although many are
connected to outside commercial and private networks.
Companies we contacted use high-speed networks for a
variety of reasons. In some cases, these networks are
used for individual applications that require high
transmission speeds, such as interactive
videoconferencing. Most companies also used these
networks as a more cost-effective way of transmitting
large volumes of aggregated traffic from lower-speed
applications. These applications include voice
communication, remote computer access, and electronic
mail.
Landmark Graphics Corporation, a company that
develops seismic data processing software for oil
exploration, for example, uses an extensive T1 network
to support a variety of applications. This network
supports up to four voice lines (at 64,000 bits per
second each), while providing electronic mail access
to hundreds of network users. This network also
allows users across the country to work simultaneously
on the development of the same software by accessing
and sharing files via high performance workstations,
and to routinely transfer voluminous files to backup
the file system. A Landmark representative said that
network use has provided more coordinated and
consistent control of product development among the
company's different offices, and ultimately, a
shortened product development life-cycle.
The Amoco Corporation uses a high-speed network to
transmit very large (100 million bit to 1 billion bit)
files between its foreign and domestic sites. The
files contain large volumes of data such as images of
sections of the earth, which measure about 400 square
miles wide by 3 miles deep. These data are critical
to improving Amoco's ability to locate oil reservoirs.
Because of the volume of the data, Amoco
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representatives said it would be impossible to
transmit these files to each work site without high-
speed networks. If they did not have the networks,
the data would have to be duplicated at each site,
resulting in higher costs. Moreover, according to an
Amoco representative, access to the supercomputer via
the high-speed network enabled them to make a major
oil discovery--the details of which are proprietary.
Within the automobile industry, a General Motors (GM)
Corporation representative reported that high-speed
networks primarily benefit them by reducing costs and
increasing productivity. For example, the network
permits resource sharing, reducing duplicate hardware
and software purchases. One group reported saving
$90,000 by using university software over the network,
rather than purchasing it. Another group reported
that it did not have to buy a parallel supercomputer
because it accessed one at a university via the
network. In addition, a corporate networking group
projected a $2.3 million cost avoidance for 1991
because the use of a high-speed network enabled them
to make large data and graphics files more readily
available to remote sites.
_____________________________________________________________________________
We discussed the information in this report with
industry representatives and experts, and
incorporated their comments where appropriate. Our
work was performed between October 1990 and May 1991.
As agreed with your office, unless you publicly
announce the contents of this report earlier, we plan
no further distribution until 30 days from the date of
this letter. We will then send copies to interested
congressional committees and others upon request.
Please contact me at (202) 275-3195 if you have any
questions concerning this report. The major
contributors to this report are listed in appendix
VIII.
Jack L. Brock, Jr.
Director
Government Information
and Financial Management
Page 9 GAO/IMTEC-91-58 Supercomputers and High-Speed Networks
_____________________________________________________________________________
CONTENTS
#####################________________________________________________________
LETTER 1
#####################________________________________________________________
Appendix I 12
OBJECTIVES, SCOPE,
AND METHODOLOGY
#####################________________________________________________________
Appendix II 13
THE OIL INDUSTRY Seismic Data Processing 13
Reservoir Simulation 15
#####################________________________________________________________
Appendix III 17
THE AEROSPACE Computational Fluid Dynamics 18
INDUSTRY Structural Analysis 19
Computational Electromagnetics 20
#####################________________________________________________________
Appendix IV 21
THE AUTOMOBILE Automobile Crash Analysis 22
INDUSTRY Structural Analysis 23
Computational Fluid Dynamics 23
#####################________________________________________________________
Appendix V 25
THE CHEMICAL AND Molecular Modeling 26
PHARMACEUTICAL Structural Analysis 27
INDUSTRIES Computational Fluid Dynamics 27
#####################________________________________________________________
Appendix VI 28
COMPANIES
INTERVIEWED REGARDING
SUPERCOMPUTER USE
#####################________________________________________________________
Appendix VII 29
COMPANIES
INTERVIEWED REGARDING
HIGH-SPEED NETWORK USE
#####################________________________________________________________
Appendix VIII 30
MAJOR CONTRIBUTORS TO
THIS REPORT
______________________________________________________
Abbreviations
ARCO Atlantic Richfield Company
GAO General Accounting Office
GM General Motors Corporation
IBM International Business Machines Corporation
IMTEC Information Management and Technology Division
NASA National Aeronautics and Space Administration
NSF National Science Foundation
Page 10 GAO/IMTEC-91-58 Supercomputers and High-Speed Networks
Appendix I
_____________________________________________________________________________
OBJECTIVES, SCOPE, AND METHODOLOGY
_____________________________________________________________________________
At the request of the Senate Subcommittee on Science,
Technology, and Space, the Senate Committee on
Commerce, Science, and Transportation; the House
Subcommittee on Technology and Competitiveness; and
the House Committee on Science, Space, and Technology;
we reviewed various industries' use of supercomputers
and high-speed networks. The purpose of our review
was to (1) illustrate how the automobile, aerospace,
petroleum, and chemical and pharmaceutical industries
are using supercomputers to improve products, reduce
costs, save time, or provide other benefits; (2)
describe barriers that inhibit the increased use of
supercomputers; and (3) provide examples of how
certain industries use high-speed networks and their
associated benefits.
To illustrate how industries are using and
benefitting from supercomputers and identify barriers
to their increased use, we interviewed managers,
scientists, and engineers from the 24 companies listed
in appendix VI. We selected these companies on the
basis of recommendations from various experts
knowledgeable about industrial supercomputer use.
Most of the companies we selected are Fortune 500
companies, largely because of the resources required
to purchase, maintain, and use supercomputers.
We also interviewed and obtained background
information on supercomputers and on industry
applications and future trends from industry analysts
and consultants, hardware vendors, and government
officials. The industry analysts and consultants
included those from Research Consortium, Inc.,
Dataquest, The Superperformance Computing Service,
Gartner Group, Inc., and the Institute for
Supercomputing Research Recruit Co., Ltd. The
hardware vendors included Cray Research, Inc.,
International Business Machines Corporation, Thinking
Machines Corporation, and Silicon Graphics, Inc. The
government officials included those from the Office of
Science and Technology Policy, International Trade
Administration, Department of Commerce, Lawrence
Livermore National Laboratory, Department of Energy,
and National Aeronautics and Space Administration Ames
Research Center, National Science Foundation (NSF),
and NSF supercomputer centers--San Diego Supercomputer
Center, National Center for Supercomputing
Applications at the University of Illinois at Urbana-
Champaign, Cornell Theory Center, and Pittsburgh
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_____________________________________________________________________________
Appendix I
Objectives, Scope, and Methodology
_____________________________________________________________________________
Supercomputing Center. We also interviewed and
obtained documents from representatives of the
Institute of Electrical and Electronics Engineers,
Inc., and the American Petroleum Institute.
To assess how industries use high-speed computer
networks, we collected information from companies in
various industries and procured the services of Texas
Internet Consulting, a firm that designs and
implements networks for large corporations. This firm
subsequently interviewed the ten computer, automobile,
and oil companies listed in appendix VII to determine
how these companies use and benefit from high-speed
networks. These companies had been selected based on
the recommendation of experts as being frequent users
of high-speed networks. Texas Internet Consulting
also provided background information on high-speed
networks and related applications.
We discussed the information in this report with
scientists, engineers, and other experts from 14 oil,
aerospace, automobile, chemical and pharmaceutical,
and computer companies and have incorporated their
views as appropriate. However, we did not verify the
validity or accuracy of the examples of dollar savings
and productivity improvements provided to us by the
various companies. In some cases, we were unable to
obtain such information because it was considered
proprietary and could not be released. In other
cases, company representatives said they had not
performed the extensive analysis necessary to quantify
such benefits.
Our review was conducted from October 1990 to May 1991
primarily in Washington, D.C., and other locations
listed in appendix VI.
Page 12 GAO/IMTEC-91-58 Supercomputers and High-Speed Networks
Appendix II
_____________________________________________________________________________
THE OIL INDUSTRY
_____________________________________________________________________________
Many large oil companies worldwide--including
American, British, French, and Middle Eastern
companies--use supercomputers to better determine the
location of oil and gas reservoirs, and to maximize
the output from these reservoirs. The oil industry is
among the early users of supercomputers, with ARCO
being the first company to purchase a Cray
supercomputer, in 1980, to model the largest oil
reservoir in the U.S.--Prudhoe Bay, Alaska. Since
that time, the oil industry has invested hundreds of
millions of dollars in developing software for
supercomputer applications. In addition, the industry
uses off-the-shelf, consultant-developed and
university-developed software.
The oil industry is now looking at massively parallel
processing to achieve the next-order-of-magnitude
improvement in speed. The industry has many large
computational problems--such as modeling entire
reservoirs in greater detail--that cannot be
practically attempted on today's supercomputers. Many
companies are experimenting with parallel
supercomputers and are converting vector software to
parallel software. According to an ARCO
representative, such conversion is time-consuming and
expensive because programs are extremely large.
Despite industry movement toward parallel
supercomputers, most representatives thought that
vector supercomputers would continue to be used to a
great extent. The oil industry uses two key
supercomputer applications--seismic data processing
and reservoir simulation--to aid in oil and gas
exploration and production. Most representatives from
the eight companies we contacted said that
supercomputers have greatly helped them reduce costs.
They also stated that supercomputers have greatly
enabled them to (1) perform previously impossible
tasks and (2) improve the quality and timeliness of
their simulations.
#####################________________________________________________________
SEISMIC DATA Seismic data processing is used to produce images of
PROCESSING subsurface geology through calculations involving
large volumes of seismic data. Analysis of these
images increases the probability of determining the
location of oil reservoirs. This is important because
the vast majority of holes drilled (ranging in cost
from $.5 million to over $50 million) are dry and this
is the most reliable way of determining the presence
of oil or gas without drilling. While two
representatives mentioned that seismic data processing
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_____________________________________________________________________________
Appendix II
The Oil Industry
_____________________________________________________________________________
had been critical in making significant oil and gas
discoveries, the details on these finds are
proprietary.
Although most representatives indicated difficulties
in estimating the economic benefits derived from using
supercomputers for seismic data processing, various
industry representatives said that it reduces the
number of dry wells drilled by about 10 percent,
saving hundreds of millions of dollars over the last 5
years. Chevron Corporation representatives stated
that it reduces drilling of dry off-shore wells by
about 50 percent. Drilling costs for the oil industry
are significant, totaling over $200 billion over the
past decade.
Using a supercomputer for seismic data processing also
permits a faster payoff for millions of dollars in
property, equipment, data collection, and other up-
front investments. An ARCO representative estimated
that it saves about a half million dollars per
development well (a well located in a known oil field)
because oil is located and recovered more quickly.
Representatives said it would be impractical to run
their seismic data processing applications on less
powerful computers. They said that supercomputers
increased the speed of results from 3 to 100 times
that of other computers, depending on the amount of
data being processed. This permits them to run more
iterations of a seismic image, which in turn improves
the image, and the quality of their drilling
decisions.
In addition, supercomputers enable these companies to
perform more complex seismic data processing tasks
than would be possible on other computers. Depth
migration and modeling reservoirs located around salt
domes are two such tasks that require massive
computations. Depth migration is a process that
removes some of the distortion of seismic images
caused by layers of rocks acting as lenses. Companies
are continually improving this method to provide more
accurate images, particularly of areas where rocks are
layered, such as in the foothills of the Rocky
Mountains.
Another recently developed process that can only be
run on supercomputers--producing accurate images
through salt--is being used by several companies to
improve their ability to discover oil in areas with
salt domes. This process is important because salt
domes are likely traps for oil. Yet, it is difficult
to get a clear view of what lies under salt domes
Page 14 GAO/IMTEC-91-58 Supercomputers and High-Speed Networks
_____________________________________________________________________________
Appendix II
The Oil Industry
_____________________________________________________________________________
because salt absorbs sound waves and distorts seismic
images. In 1987, Oryx Energy Company used a Cray X-MP
to better understand the shape of salt domes. While
they had previously thought the domes were
cylindrical, supercomputer simulations revealed that
they were smaller and mushroom-shaped. Understanding
their shape enabled Oryx to change their drilling path
and discover oil in a well in the Mississippi Salt
Basin.
#####################________________________________________________________
RESERVOIR SIMULATION Reservoir simulation, an important tool used to
increase the amount of oil and gas that can be
extracted from a reservoir, allows engineers to
"experiment" on a field by trying out various
recovery methods and sizes and types of facilities
(i.e., equipment used in extraction). By analyzing
the alternatives, the most cost-beneficial development
methods for a field can be identified before the
actual production work is undertaken. The importance
of reservoir simulation derives from the need for
long-term optimization of recovery of the world's
limited fuel resources.
Although representatives said that it is difficult to
estimate the economic benefits derived from
supercomputing in reservoir simulation, various
representatives said that it permits increased oil
yield, which one representative estimated to be worth
$10 million annually to their company. One Amoco
Production Company representative estimated that the
increased yield due to reservoir simulation was about
25 percent for some wells. Simulation also reduces
the risk of losing the oil in a reservoir during
production--if the oil in a well is produced too fast,
it may move to another area of the reservoir and be
lost beyond recovery. Using supercomputers for
reservoir simulation also reduces the amount of money
spent on unnecessary recovery methods and facilities
and equipment. These methods and facilities are
expensive--recovery methods cost from about $1 to $25
per barrel, while surface facilities and equipment for
a very large field can cost billions of dollars.
Investment in the wrong recovery methods and
facilities can break a company.
Supercomputers have enabled the industry to perform
reservoir simulations of entire large fields,
previously considered too impractical or costly.
Full-field models of Prudhoe Bay and Kuparuk, Alaska--
the largest and third largest on-shore fields in the
U.S.--were used to improve recovery methods. An ARCO
representative estimated, conservatively, that
reservoir simulation used for these oil fields has
Page 15 GAO/IMTEC-91-58 Supercomputers and High-Speed Networks
_____________________________________________________________________________
Appendix II
The Oil Industry
_____________________________________________________________________________
resulted in about a 500 million barrel increase in
production, worth between $5 billion and $10 billion.
Page 16 GAO/IMTEC-91-58 Supercomputers and High-Speed Networks
Appendix III
_____________________________________________________________________________
THE AEROSPACE INDUSTRY
_____________________________________________________________________________
Aerospace companies were among the earliest users of
supercomputers, which are regarded as essential tools
in the design, development, and testing of aircraft,
missiles, and other aerospace vehicles and components.
Furthermore, representatives generally consider
supercomputing critical to competing for advanced
military and other contracts. Of the six American
companies we contacted, four began using vector
supercomputers in the early 1980s, and by the late
1980s all had at least one supercomputer.
Most of the aerospace software applications were
initially developed in federal government
laboratories. For example, NASTRAN, one of the early
software programs for analyzing the structure and
shape of an object, was developed through research
sponsored by the National Aeronautics and Space
Administration (NASA) in the mid-1960s. Supercomputer
software is commercially available for some aerospace
applications, but companies also use software
programs developed by government facilities, and
develop or modify software for proprietary use.
Since 1987, five of the six companies have begun
experimenting with massively parallel supercomputers
to determine how to best use them and to develop
application software. One of the companies has a
massively parallel supercomputer dedicated to
classified military projects. Company representatives
indicated that in the future, their companies expect
to use massively parallel supercomputers to a greater
extent, primarily for computational fluid dynamics--an
application that permits engineers to simulate wind
tunnels. However, the lack of software is currently
limiting use of this technology.
The major supercomputer applications used by the
aerospace industry are computational fluid dynamics,
structural analysis, and computational
electromagnetics. Most companies we contacted
reported that these applications allowed them to
perform previously impossible tasks, improve the
quality of products, and reduce the time required to
make products commercially available. For example, a
Lockheed Aerospace representative said that
supercomputers allow engineers to perform analyses in
areas of fluid dynamics, in which it is impossible to
conduct physical tests. A McDonnell Douglas
representative stated that supercomputers help
Page 17 GAO/IMTEC-91-58 Supercomputers and High-Speed Networks
_____________________________________________________________________________
Appendix III
The Aerospace Industry
_____________________________________________________________________________
engineers improve product quality by permitting them
to perform analyses and simulations much faster and
over a broader range of parameters.
#####################________________________________________________________
COMPUTATIONAL FLUID Computational fluid dymanics models enable aerospace
DYNAMICS engineers to simulate the flow of air and fluid
around and through proposed structures and components.
For instance, engineers can simulate the performance
of aircraft and other aerospace vehicles in a wind
tunnel. In addition, the performance of other
components, such as engines and electrical systems,
are simulated using this application. Prior to
supercomputers, engineers primarily evaluated
aerodynamic designs by testing physical models in wind
tunnels and assessing the aircraft during actual
flight tests. However, by using a supercomputer,
engineers can determine the effectiveness of an
aerodynamic design and make modifications before
constructing physical models.
Boeing Aircraft Company, for example, used
computational fluid dynamics extensively in the
design of its newest commercial airplane, the Boeing
777.#4 The company's chief researcher in
aerodynamics attributes a faster and more efficient
design of this airplane to using computational fluid
dynamics on a supercomputer. Those engineers
designing the shape of the airplane and those studying
its aerodynamics were able to work on the same model
simultaneously prior to constructing physical models.
Before the use of a supercomputer, these two efforts
were done sequentially, relying on physical models and
actual wind tunnel tests, which added months to the
process.
Boeing was also able to make a computer-generated
model of the Boeing 777, rather than a physical model,
available to potential customers during the design
process. As a result, customer requests for changes
were more easily accommodated. For example, one
request made during the design phase caused Boeing to
redesign a fold in the airplane's wings so that the
wing tips would raise, allowing the airplane to fit
through existing airport gates. Using computational
fluid dynamics on a Cray Y-MP supercomputer, Boeing
engineers quickly evaluated three potential designs
and identified the configuration with the right
______________________________________________________
4 Boeing announced the development of the 777
aircraft in 1990 and plans to make its first delivery
in 1995.
Page 18 GAO/IMTEC-91-58 Supercomputers and High-Speed Networks
_____________________________________________________________________________
Appendix III
The Aerospace Industry
_____________________________________________________________________________
balance of aerodynamic efficiency, structural weight,
and cost. Boeing's confidence in the results is
evidenced by the fact that it committed the wing
design to production before conducting physical wind
tunnel tests.
In addition, Lockheed Aeronautical Systems Company
used computational fluid dynamics on a Cray X-MP
supercomputer to develop a computer model of the
Advanced Tactical Fighter for the U.S. Air Force. In
about 5 hours of processing time, Lockheed simulated
the fighter's performance using a full-vehicle
computer model to obtain aerodynamic data that is
normally only provided through actual wind tunnel
testing. By using the supercomputer simulations,
Lockheed shortened the development phase of the
prototype fighter by several months and reduced the
amount of traditional wind tunnel testing by 80 hours.
The latter resulted in savings of about a half
million dollars.
McDonnell Douglas found that using computational
fluid dynamics on a supercomputer to simulate the
performance of the C-17 military aircraft reduced
design and wind tunnel testing time. Engineers used
this application to analyze 76 potential wing
configurations and identify the best three designs.
Thus, they only had to conduct traditional wind tunnel
tests on the final three designs. This complete
process required 9 months and 350 hours of wind tunnel
testing. In contrast, designing the wings of the DC-
10 commercial airplane without using this
supercomputer application, took 2 years and required
1,200 hours of wind tunnel testing on more than 50
designs.
#####################________________________________________________________
STRUCTURAL ANALYSIS Aerospace companies also use supercomputers to
analyze the structure of aircraft and other aerospace
vehicles and components to determine optimum weight,
shape, and composition. Structural analysis
applications simulate the stresses and strains on a
given object that result from applied pressure or
loads. The structure of an object, such as an
aircraft, is first defined as a grid of elements
representing its shape and composition. Engineers can
then use the model to ascertain the effects of
pressure and loads on each element of the structure
(e.g., metal fatigue). The supercomputer permits the
analysis to be done quicker and more often than
performing physical tests on actual structures.
Page 19 GAO/IMTEC-91-58 Supercomputers and High-Speed Networks
_____________________________________________________________________________
Appendix III
The Aerospace Industry
_____________________________________________________________________________
McDonnell Douglas engineers, for example, uncovered
and corrected a helicopter fan design flaw in 2 days
on their Cray X-MP supercomputer, after spending 6
weeks trying to uncover the problem using other
computers. The design flaw concerned the level and
location of stress experienced within the helicopter
fan hub when spinning. (A fan hub looks similar to a
wheel on an automobile and generates air flow inside
the tail of a helicopter.) Using structural
analysis, engineers were able to identify the fan
hub's high-stress areas and make the necessary design
modifications.
#####################________________________________________________________
COMPUTATIONAL Supercomputers have also been used to simulate
ELECTROMAGNETICS the electromagnetic characteristics of military
aircraft to make them more difficult to detect using
radar. The supercomputer models the chemical
composition of the aircraft's outer surface, the
geometry of the aircraft, and the reflections of
electromagnetic waves off the aircraft's outer
surface.
Lockheed Aeronautical Systems Company, for example,
reduced the radar signature (the size of an image
appearing on a radar display) of a low-observable,
stealth-like military aircraft, using computational
electromagnetics on Cray X-MP and Cray Y-MP
supercomputers. This reduced the signature
substantially beyond what had been previously obtained
using other means. As a result, Lockheed was able to
construct fewer physical models and conduct fewer
physical electromagnetic tests at a savings of $4.4
million and $1.5 million, respectively.
Page 20 GAO/IMTEC-91-58 Supercomputers and High-Speed Networks
Appendix IV
_____________________________________________________________________________
THE AUTOMOBILE INDUSTRY
_____________________________________________________________________________
Automobile manufacturers have been using
supercomputers increasingly since 1984 as a design
tool to make cars safer, lighter, more economical, and
better built, with significant time and dollar
savings. By 1989, each of the 12 largest automobile
companies worldwide had acquired one or more Cray
supercomputers. These supercomputers are enabling
automotive engineers to create increasingly
sophisticated and realistic simulation models to
design and test future vehicles. It would be
impractical to perform many of these simulations, such
as large three-dimensional models, on anything less
powerful than a supercomputer.
Although commercial supercomputer software is
available for most automotive applications, much of
this software originated from federally-supported
research. For example, KIVA, a computer program
developed at Los Alamos National Laboratory, is used
to model, in three dimensions, the interactions of air
and liquids flowing through an engine. NASTRAN,
developed under the sponsorship of NASA, is used to
analyze various automobile structures. DYNA3D,
developed at Lawrence Livermore National Laboratory,
is used to simulate car crashes. Commercial vendors
and the automobile companies have also modified these
applications to meet specific needs of the automobile
industry.
Although no companies reported owning massively
parallel supercomputers, some of these companies were
exploring the potential of this new technology. Some
company representatives indicated that massively
parallel supercomputers will be important in order to
process larger and more complex models, particularly
for crash analysis and computational fluid dynamics.
The primary applications used by the automobile
industry are automobile crash analysis, structural
analysis, and computational fluid dynamics. The five
companies we contacted--both American and Japanese--
reported that these applications have had a moderate
to great impact on improving product quality, reducing
costs, and performing previously intractable tasks.
According to a Ford Motor Company representative, the
intense competitiveness of the industry has made it
necessary to use a supercomputer. A Nissan Motor
Company representative also stated that Nissan would
Page 21 GAO/IMTEC-91-58 Supercomputers and High-Speed Networks
_____________________________________________________________________________
Appendix IV
The Automobile Industry
_____________________________________________________________________________
not consider developing automobiles without a
supercomputer.
#####################________________________________________________________
AUTOMOBILE CRASH Crash analysis is one of the primary applications for
ANALYSIS supercomputers in the automotive industry because it
provides an alternative to physically crashing test
vehicles. The primary advantage of modeling a crash
on a supercomputer is that more data about the crash
is produced at a cost and within a time frame that
would be otherwise impossible to achieve. For
example, crash simulations can show how the vehicle
structure will collapse during a crash, how fast the
driver and passengers will move forward during impact,
and when air bag sensors will be activated.
Initially, vehicle crash simulations involved
modeling a half-car frontal crash. Today's models
have become more complex, involving full vehicle
crashes, two full vehicle crashes, and side impact
crashes. Using these models, companies can then
compare many more designs and optimize a vehicle's
structure for weight, stiffness, and strength before a
full prototype vehicle is crash tested.
Physical crash tests require prototype vehicles,
which are time- consuming and expensive to
manufacture. According to one automobile company,
each test costs between $50,000 and $750,000,
depending on whether a production vehicle or a
prototype is used. In addition, a prototype vehicle
can take as long as 8 months to manufacture. In
contrast, full car crash simulations can be processed
on a supercomputer in less than 20 hours.
According to General Motors Corporation (GM)
representatives, crash testing prototype vehicles has
been substantially reduced as a result of
supercomputing. In testing passenger restraint
devices, such as seat belts, during the development of
some of its 1992 automobiles, GM crashed about 100
fewer vehicles than it did in 1987. According to
company representatives, the reduction was largely due
to crash simulations on a Cray supercomputer.
In addition, the Saturn Corporation, a subsidiary of
GM, estimated that they performed over 100 vehicle
crash simulations on a supercomputer between 1986 and
1990. Data obtained from these simulations were then
used to modify the design of the vehicles. As a
result, Saturn reported a savings of more than $2
million in development and test costs.
Page 22 GAO/IMTEC-91-58 Supercomputers and High-Speed Networks
_____________________________________________________________________________
Appendix IV
The Automobile Industry
_____________________________________________________________________________
#####################________________________________________________________
STRUCTURAL ANALYSIS Automobile companies use structural analysis
models to simulate the physical structure of an
automobile, including parts and components, to
improve functionality and reduce manufacturing costs.
The simulations help engineers design stronger parts
that are lighter and less susceptible to problems
caused by vibration and stress. Lighter parts also
contribute to improvements in fuel economy.
Chrysler Corporation improved the design of a small
car's body structure and a convertible's floor
structure by modeling them on a Cray X-MP
supercomputer. The stiffness of the small car body
structure was improved by 10 percent, while its weight
was reduced by 45 pounds. The improvement in body
stiffness on the small car made the vehicle easier to
handle and gave it a better ride. The floor of the
convertible was lengthened by 8 percent, yet reduced
in weight by 9 pounds. Chrysler estimates that it
will save about $3.9 million annually in reduced raw
materials to manufacture both vehicles.
Chrysler was also able to eliminate the need for a
dash board bracket in a new minivan by modeling the
dash board structure on a Cray X-MP supercomputer.
The model showed that the remaining dash board
brackets were sufficient to hold the dash board
structure in place. Chrysler estimates that the
elimination of the $2 bracket will save about $940,000
annually in the cost of parts to manufacture the
vehicle.
In addition, Chrysler improved the design of a new 2.0
liter engine by modeling its structure on a Cray X-MP
supercomputer. The stiffness, or rigidity, of the
engine structure was increased by 3 percent, thus
contributing to a smoother running engine. In
addition, its overall weight was reduced by 9 pounds.
Chrysler estimates that it will save about $1.8
million annually in reduced raw materials to
manufacture the engine.
#####################________________________________________________________
COMPUTATIONAL FLUID Computational fluid dynamic models are used to
DYNAMICS simulate the flow of air or liquids around or through
automobile parts or structures. Specifically, models
simulate the exterior flow of air around a vehicle,
the flow of air within the vehicle, and the flow of
air and liquids within the engine, cooling system, and
air conditioning system.
At Chrysler Corporation, for example, engineers used a
Cray X-MP supercomputer to simulate the flow of
Page 23 GAO/IMTEC-91-58 Supercomputers and High-Speed Networks
_____________________________________________________________________________
Appendix IV
The Automobile Industry
_____________________________________________________________________________
liquids through the cooling system of one of its
vehicles. This analysis helped determine which design
was most efficient in cooling the vehicle's engine.
Thus, the design of the system was optimized to
improve its cooling efficiency while reducing the
number of needed parts. Chrysler estimates that this
reduction will reduce manufacturing costs by about 5
percent, saving about $1.6 million annually.
Page 24 GAO/IMTEC-91-58 Supercomputers and High-Speed Networks
Appendix V
_____________________________________________________________________________
THE CHEMICAL AND PHARMACEUTICAL INDUSTRIES
_____________________________________________________________________________
The chemical and pharmaceutical industries are the
fastest-growing group of industrial supercomputer
users, although their use is still in its infancy.
The impetus for these industries to begin using
supercomputers was a combination of recent advances in
theoretical chemistry and three-dimensional
visualization techniques. Du Pont became the first
company in these industries to buy a vector
supercomputer in 1986. Since then, several other
American and Japanese companies have begun using
supercomputers. Two companies--Dow Chemical Company
and Eli Lilly & Company--are now experimenting with
massively parallel supercomputers. Lilly is using a
supercomputer at the National Center for
Supercomputing Applications--a NSF supercomputer
center at the University of Illinois--to develop code
to be used on massively parallel supercomputers.
Some of the important chemical software applications
used today were derived from applications developed at
government laboratories, such as NASA Ames Research
Center. However, little application software has been
available until very recently, because the chemical
industry only recently began using supercomputers. In
order to develop sophisticated application software on
a reduced, shared-cost basis, Cray Research, Inc.,
other vendors, chemical companies, and government
laboratories have formed a chemical software
consortium. Member companies include Lilly, Monsanto
Company, Exxon Research and Engineering, Du Pont, and
3M Corporation.
The major supercomputer applications in the chemical
and pharmaceutical industries include molecular
modeling, structural analysis, and computational fluid
dynamics, and are used in basic research, product
development, manufacturing process design,
manufacturing plant design, environmental impact
assessment, and waste disposal. Thus, supercomputing
affects many stages of the industry's product lines.
These product lines number in the thousands and
include industrial chemicals, polymers,#5 and
biological materials for agriculture and medicine.
All company representatives reported that the use of
______________________________________________________
5 A chemical compound or mixture of compounds
containing repeated structural units of the same
original molecules, such as Nylon.
Page 25 GAO/IMTEC-91-58 Supercomputers and High-Speed Networks
_____________________________________________________________________________
Appendix V
The Chemical and Pharmaceutical Industries
_____________________________________________________________________________
supercomputers greatly helps them perform previously
intractable tasks--such as the study of complex
molecules. Several representatives also said that
supercomputers helped them reduce cost and time to
market, improve quality, and develop a greater variety
of products.
#####################________________________________________________________
MOLECULAR MODELING Molecular simulations enable scientists to study the
molecular properties of chemical compounds used in the
development of drugs and other products. One of the
keys to understanding molecules lies in gaining a
clear appreciation of their three-dimensional shape.
Unlike the rigid "ball and stick" models that
scientists built in the past, the atomic positions in
a molecule are constantly changing. Using
supercomputers in conjunction with workstations,
scientists are able to construct images, such as
those of large, complex human proteins and enzymes.
Scientists can then rotate these images to gain clues
on biological activity and reactions to various drug
candidates.
The use of molecular modeling has also been
important, from an economic perspective, in the
development of new drugs. A Du Pont scientist
estimated that about 30,000 compounds are
synthesized--at a cost of about $5,000 per synthesis
and initial screening--for every new drug that is
developed. As such, as much as $150 million can be
invested in discovering a drug, even before clinical
testing, federal government approval, and
manufacturing and development costs are added. By
making this drug discovery process more "rational,"
with less trial and error, a Du Pont representative
estimates that millions of dollars can be saved.
Du Pont is currently developing replacements for
chlorofluorocarbons, compounds used as coolants for
refrigerators and air conditioners, and as cleansing
agents for electronic parts. These compounds are
being phased out because they are thought to
contribute to the depletion of ozone in the
atmosphere. Du Pont is designing a new process to
produce substitute compounds safely and cost-
effectively. These substitutes will be more reactive
in the atmosphere and will decompose faster. Du Pont
is using a supercomputer to calculate the
thermodynamic data needed for developing this process.
These calculations can be completed by the
supercomputer in a matter of days, at an approximate
cost of $2,000 to $5,000. Previously, such tests were
conducted in a laboratory, and required up to 3 months
to conduct, at a cost of about $50,000. Both the
Page 26 GAO/IMTEC-91-58 Supercomputers and High-Speed Networks
_____________________________________________________________________________
Appendix V
The Chemical and Pharmaceutical Industries
_____________________________________________________________________________
cost and time required for such traditional methods
would have substantially limited the amount of testing
that is now being done.
#####################________________________________________________________
STRUCTURAL ANALYSIS Computer-based structural analysis techniques are used
in the chemical and pharmaceutical industries to
determine stress and durability of both products and
processing equipment. For example, Du Pont engineers
used structural analysis to optimize the design of a
mold used in a new process for manufacturing Corian#6
sinks. This enabled them to quickly determine the
wall thicknesses, ribbing, and reinforcements
necessary to withstand the molding pressure while
minimizing its weight. Thus, this application enabled
them to develop the manufacturing process 6 to 12
months sooner than would have been possible using a
series of prototype molds. This saved development
costs and increased revenue by getting the new process
in operation faster.
#####################________________________________________________________
COMPUTATIONAL FLUID The chemical and pharmaceutical industries use
DYNAMICS computational fluid dynamics to model products and
product performance, and to aid in the design of
manufacturing processes and plants. These models
predict how fluids flow through equipment and can
simulate processes, such as mixing, drying, cooling,
and separation. For example, Du Pont has successfully
used this application on a Cray Y-MP supercomputer to
model manufacturing processes for sheet products, such
as film and plastic wrappers. These products,
particularly X-ray film, must be uniform in thickness
to meet the required quality standard. Thus,
computational fluid dynamics provides Du Pont with an
additional design tool to improve sheet product
thickness uniformity, without increasing manufacturing
time.
Du Pont also models the manufacturing process for
Nylon, one of its major products. Computational fluid
dynamics solutions to these models accurately quantify
the flow through the processing equipment and locates
where clogging is most likely to occur. Clogging is a
major problem in Nylon plants, causing periodic
shutdowns. By modeling the process, Du Pont has been
able to reduce the number of shutdowns.
______________________________________________________
6 Corian is a registered trademark of E.I. du
Pont de Nemours and Company.
Page 27 GAO/IMTEC-91-58 Supercomputers and High-Speed Networks
Appendix VI
_____________________________________________________________________________
COMPANIES INTERVIEWED REGARDING
SUPERCOMPUTER USE
_____________________________________________________________________________
Aerospace Companies The Boeing Company, Seattle, Washington
General Dynamics Corporation, Fort Worth, Texas
Grumman Corporation, Bethpage, New York
Lockheed Corporation, Calabasas, California
McDonnell Douglas Corporation, Hazelwood, Missouri
Pratt & Whitney, United Technologies Corporation,
East Hartford, Connecticut
_____________________________________________________________________________
Automobile Companies Chrysler Corporation, Highland Park, Michigan
Ford Motor Company, Dearborn, Michigan
General Motors Corporation, Warren, Michigan
Honda Motor Company, Ltd., Tokyo, Japan
Nissan Motor Company, Ltd., Tokyo, Japan
_____________________________________________________________________________
Chemical and Dow Chemical Company, Champaign, Illinois
Pharmaceutical E.I. du Pont de Nemours and Company, Wilmington,
Companies Delaware
Eli Lilly & Company, Indianapolis, Indiana
Merck & Company, Rahway, New Jersey
Monsanto Company, St. Louis, Missouri
_____________________________________________________________________________
Petroleum Companies Amoco Production Company, Tulsa, Oklahoma
Atlantic Richfield Company (ARCO), Plano, Texas
British Petroleum (BP), Houston, Texas
Chevron Corporation, Houston, Texas
Exxon Production Research Company, Houston, Texas
Oryx Energy Company, Dallas, Texas
Phillips Petroleum Company (Phillips 66),
Bartlesville, Oklahoma
Shell Oil Company, Houston, Texas
Page 28 GAO/IMTEC-91-58 Supercomputers and High-Speed Networks
Appendix VII
_____________________________________________________________________________
COMPANIES INTERVIEWED REGARDING HIGH-SPEED
NETWORK USE
_____________________________________________________________________________
Amoco Production Company, Houston, Texas
Apple Computer, Inc., Cupertino, California
General Motors Research Corporation, Warren, Michigan
Hewlett-Packard Company, Cupertino, California
Intel Corporation, San Jose, California
International Business Machines Corporation, Austin,
Texas
Landmark Graphics Corporation, Houston, Texas
Schlumberger Well Services, Houston, Texas
Sun Microsystems, Inc., Milpitas, California
Tandem Computers, Inc., Cupertino, California
Page 29 GAO/IMTEC-91-58 Supercomputers and High-Speed Networks
Appendix VIII
_____________________________________________________________________________
MAJOR CONTRIBUTORS TO THIS REPORT
#####################________________________________________________________
INFORMATION Linda D. Koontz, Assistant Director
MANAGEMENT AND Valerie C. Melvin, Assignment Manager
TECHNOLOGY DIVISION, Beverly A. Peterson, Evaluator-in-Charge
WASHINGTON, D.C. Nancy M. Kamita, Computer Scientist
#####################________________________________________________________
LOS ANGELES REGIONAL Allan Roberts, Assistant Director
OFFICE Ambrose A. McGraw, Regional Assignment Manager
Benjamin H. Mannen, Senior Evaluator
Shawnalynn R. Smith, Staff Evaluator
#####################________________________________________________________
SAN FRANCISCO Frank Graves, Regional Assignment Manager
REGIONAL OFFICE Don Porteous, Staff Evaluator
(510626)
Page 30 GAO/IMTEC-91-58 Supercomputers and High-Speed Networks
