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              United States General Accounting Office
 Testimony
 GAO


 Supercomputing in Industry


 For Release on Delivery
 Expected at 2:00 p.m. EST Tuesday, March 5, 1991


 Statement for the record by
 Jack L. Brock, Jr.,
 Director Government Information and Financial Management Issues
 Information Management and Technology Division



 Before the Subcommittee on Science, Technology, and Space
 Committee on Commerce, Science, and Transportation
 United States Senate


 GA/T-IMTEC-91-3


 Messrs. Chairman and Members of the Committee and Subcommittee:


 I am pleased to submit this statement for the record, as part of the
 Committee's hearing on the proposed High Performance Computing
 Act of 1991. The information contained in this statement reflects the
 work that GAO has conducted to date on its review of how industries
 are using supercomputers to improve productivity, reduce costs, and
 develop new products. At your request, this work has focused on
 four specific industries--oil, aerospace, automobile, and
 pharmaceutical/chemical--and was limited to determining how these
 industries use supercomputers and to citing reported benefits.

 We developed this material through an extensive review of
 published documents and through interviews with knowledgeable
 representatives within the selected industries. In some cases, our
 access to proprietary information was restricted. Since this statement
 for the record reports on work still in progress, it may not fully
 characterize industry use of supercomputers, or the full benefits
 likely to accrue from such use.

 BACKGROUND

 A supercomputer, by its most basic definition, is the most powerful
 computer available at a given time. While the term supercomputer
 does not refer to a particular design or type of computer, the basic
 design philosophy emphases vector or parallel processing,

 [Footnote 1: Vector processing provides the capability of operating on
 arrays, or vectors, of information simultaneously. With parallel
 processing, multiple parts of a program are executed concurrently.
 Massively parallel supercomputers are currently defined as those
 having over 1,000 processors.]

 aimed at achieving high levels of calculation very rapidly. Current
 supercomputers, ranging in cost from $1 million to $30 million, are
 capable of performing hundreds of millions or even billions of
 calculations each second. Computations requiring many hours or days
 on more conventional computers may be accomplished in a few
 minutes or seconds on a supercomputer.

 The unique computational power of supercomputers makes it
 possible to find solutions to 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 centers around scientific visualization, a technique
 allowing researchers to plot masses of raw data in three dimensions
 to create visual images of objects or systems under study. This
 enables researchers to model abstract data, allowing them to "see"
 and thus comprehend more readily what the data reveal.

 While still relatively limited in use, the number of supercomputers
 has risen dramatically over the last decade. In the early l980s, 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

 [Footnote 2: 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.]

 are in use worldwide. 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.

 The industries we are examining enjoy a reputation for using
 supercomputers to solve complex problems for which solutions might
 otherwise be unattainable. Additionally, they represent the largest
 group of supercomputer users. Over one-half of the 280
 supercomputers in operation are being used for oil exploration;
 aerospace modeling, testing, and development; automotive testing
 and design; and chemical and pharmaceutical applications.

 THE OIL INDUSTRY

 The oil industry uses supercomputers to better determine the
 location of oil reservoirs and to maximize the recovery of oil from
 those reservoirs. Such applications have become increasingly
 important because of the low probability of discovering large oil
 fields in the continental United States. New oil fields are often small,
 hard to find, and located in harsh environments making exploration
 and production difficult. The oil industry uses two key
 supercomputer applications, seismic data processing and reservoir
 simulation, to aid in oil exploration and production. These
 applications have saved money and increased oil production.

 Seismic data processing increases the probability of determining
 where oil reservoirs are located by analyzing large volumes of
 seismic data

 [Footnote 3:  Seismic data are gathered by using sound-recording
 devices to measure the speed at which vibrations travel through the
 earth.]

 and producing two and three- dimensional images of subsurface
 geology. Through the study of these images, geologists can better
 understand the characteristics of the area, and determine the
 probability of oil being present. More accurately locating oil
 reservoirs is important because the average cost of drilling a well is
 estimated at about $5.5 million and can reach as high as $50 million.
 Under the best of circumstances, most test wells do not result in
 enough oil to make drilling cost-effective. Thus, avoiding drilling one
 dry well can save millions of dollars. The industry representatives
 who agreed to share cost estimates with us said that supercomputer
 use in seismic data processing reduces the number of dry wells
 drilled by about 10 percent, at a savings of hundreds of millions of
 dollars over the last 5 years.

 Reservoir simulation is used to increase the amount of oil that can be
 extracted from a reservoir. Petroleum reservoirs are accumulations
 of oil, water, and gas within the pores of rocks, located up to several
 miles beneath the earth's surface. Reservoir modeling predicts the
 flow of fluids in a reservoir so geologists can better determine how
 oil should be extracted.  Atlantic Richfield and Company (ARCO)
 representatives estimate that reservoir simulation used for the oil
 field at Prudhoe Bay, Alaska--the largest in production in the United
 States--has resulted in increased oil production worth billions of
 dollars.

 THE AEROSPACE INDUSTRY

 Engineers and researchers also use supercomputers to design,
 develop, and test aerospace vehicles and related equipment. In
 particular, computational fluid dynamics, which is dependent upon
 supercomputing, enables engineers to simulate the flow of air and
 fluid around proposed design shapes and then modify designs
 accordingly. The simulations performed using this application are
 valuable in eliminating some of the traditional wind tunnel tests
 used in evaluating the aerodynamics of airplanes. Wind tunnels are
 expensive to build and maintain, require costly construction of
 physical models, and cannot reliably detect certain airflow
 phenomena. Supercomputer-based design has thus resulted in
 significant time and cost savings, as well as better designs, for the
 aerospace industry.

 Lockheed Aerospace used computational fluid dynamics on a
 supercomputer to develop a computer model of the Advanced
 Tactical Fighter for the U.S. Air Force. By using this approach,
 Lockheed was able to display a full-vehicle computer model of the
 fighter after approximately 5 hours of supercomputer processing
 time. This approach allowed Lockheed to reduce the amount of wind-
 tunnel testing by 80 hours, resulting in savings of about half a
 million dollars.

 The Boeing Aircraft Company used a Cray 1S-2000 supercomputer to
 redesign the 17-year old 737-200 aircraft in the early 1980s. Aiming
 to create a more fuel-efficient plane, Boeing decided to make the
 body design longer and replace the engines with larger but more
 efficient models. To determine the appropriate placement of these
 new engines, Boeing used the supercomputer to simulate a wind-
 tunnel test. The results of this simulation--which were much more
 detailed than would have been available from an actual wind-tunnel
 test--allowed the engineers to solve the engine placement problem
 and create a more fuel-efficient aircraft.

 THE AUTOMOBILE INDUSTRY

 Automobile manufacturers have been using supercomputers
 increasingly since 1985 as a design tool to make cars safer, lighter,
 more economical, and better built. Further, the use of
 supercomputers has allowed the automobile industry to achieve
 these design improvements at significant savings.

 One supercomputer application receiving increasing interest is
 automobile crash-simulation. To meet federally mandated crash-
 worthiness requirements, the automobile industry crashes large
 numbers of pre-prototype vehicles head-on at 30 miles per hour into
 rigid barriers. Vehicles for such tests can cost from $225,000 to
 $750,000 each. Crash simulation using supercomputers provides
 more precise engineering information, however, than is typically
 available from actually crashing vehicles. In addition, using
 supercomputers to perform this type of structural analysis reduces
 the number of actual crash tests required by 20 to 30 percent, saving
 the companies millions of dollars each year. Simulations such as this
 were not practical prior to the development of vector
 supercomputing because of the volume and complexity of data
 involved.

 Automobile companies credit supercomputers with improving
 automobile design in other ways as well. For example, Chrysler
 Corporation engineers use linear analysis and weight optimization
 software on a Cray X-MP supercomputer to improve the design of its
 vehicles. The resulting designs--which, according to a Chrysler
 representative, would not have been practical without a
 supercomputer--will allow Chrysler to achieve an annual reduction
 of about $3 million in the cost of raw materials for manufacturing its
 automobiles. In addition, one automobile's body was made 10
 percent more rigid (which will improve ride and handling) and 11
 percent lighter (which will improve fuel efficiency). According to the
 Chrysler representative, this is typical of improvements that are
 being achieved through the use of its supercomputer.

 THE CHEMICAL AND PHARMACEUTICAL INDUSTRIES

 Supercomputers play a growing role in the chemical and
 pharmaceutical industries, although their use is still in its infancy.
 From computer-assisted molecular design to synthetic materials
 research, companies in these fields increasingly rely on
 supercomputers to study critical design parameters and more
 quickly and accurately interpret and refine experimental results.
 Industry representative told us that, as a result, the use of
 supercomputing will result in new discoveries that may not have
 been possible otherwise.

 The pharmaceutical industry is beginning to use supercomputers as a
 research tool in developing new drugs. Development of a new drug
 may require up to 30,000 compounds being synthesized and
 screened, at a cost of about $5,000 per synthesis. As such, up to $150
 million, before clinical testing and other costs, may he invested in
 discovering a new drug, according to an E.I. du Pont de Nemours and
 Company representative. Scientists can now eliminate some of this
 testing by using simulation on a supercomputer. The supercomputer
 analyzes and interprets complex data obtained from experimental
 measurements. Then, using workstations, scientists can construct
 three-dimensional models of the large, complex human proteins and
 enzymes on the computer screen and rotate these images to gain
 clues regarding biological activity and reactions to various potential
 drugs.

 Computer simulations are also being used in the chemical industry to
 replace or enhance more traditional laboratory measurements. Du
 Pont is currently working to develop replacements for
 chlorofluorocarbons, compounds used as coolants for refrigerators
 and air conditioners, and as cleansing agents for electronic
 equipment. These compounds are generally thought to contribute to
 the ozone depletion of the atmosphere and are being phased out. Du
 Pont is designing a new process to produce substitute compounds in
 a safe and cost- effective manner. These substitutes will be more
 reactive in the atmosphere and subject to faster decomposition. Du
 Pont is using a supercomputer to calculate the thermodynamic data
 needed for developing the 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--using
 experimental measurements conducted in a laboratory--would
 require up to 3 months to conduct, at a cost of about $50,000. Both
 the cost and time required would substantially limit the amount of
 testing done.

 BARRIERS TO GREATER USE OF SUPERCOMPUTERS

 These examples demonstrate the significant advantages in terms of
 cost savings, product improvements, and competitive opportunity
 that can he realized through supercomputer use. However, such use
 is still concentrated in only a few industries. Our industry contacts
 identified significant, interrelated barriers that individually or
 collectively, limit more widespread use of supercomputers.

 Cost.  Supercomputers are expensive. A supercomputer's cost of
 between $1 million and $30 million does not include the cost of
 software development, maintenance, or trained staff.


 Cultural resistance.  Simulation on supercomputers can not only
 reduce the physical testing, measurement, and experimentation, but
 can provide information that cannot otherwise be attained. For many
 scientists and managers this represents a dramatic break with past
 training, experience, generally accepted methods, or common
 doctrine. For some, such a major shift in research methodology is
 difficult to accept. These new methods are simply resisted or ignored.

 Lack of application software. Supercomputers can be difficult to use.
 For many industry applications, reliable software has not yet been
 developed. This is particularly true for massively parallel
 supercomputers.

 Lack of trained scientists in supercomputing. Between 1970 and
 1985, university students and professors performed little of their
 research on supercomputers. For 15 years, industry hired students
 from universities who did not bring supercomputing skills and
 attitudes into their jobs. Now, as a result, many high-level scientists,
 engineers, and managers in industry have little or no knowledge of
 supercomputing.

 In conclusion, our work to date suggests that the use of
 supercomputers has made substantial contributions in key U.S.
 industries. While our statement has referred to benefits related to
 cost reduction and time savings, we believe that supercomputers will
 increasingly be used to gain substantive competitive advantage.
 Supercomputers offer the potential--still largely untapped--to
 develop new and better products more quickly. This potential is just
 beginning to be explored, as are ways around the barriers that
 prevent supercomputers from being more fully exploited.