An Overview of Supercomputing at General Motors Corporation
Myron Ginsberg currently serves as Consultant Systems Engineer at the Electronic Data Systems Advanced Computing Center, General Motors Research and Environmental Staff, Warren, Michigan. Until May 1992, he was Staff Research Scientist at General Motors Research Laboratories.
During a 13-year tenure at General Motors, Dr. Ginsberg was significantly involved in GM's initial and continuing supercomputer efforts, which led to the first installation of a Cray supercomputer in the worldwide auto industry. He is also Adjunct Associate Professor in the Electrical Engineering and Computer Science Department, College of Engineering, at the University of Michigan. He has edited four volumes on vector/parallel computing applications in the auto industry. He has three times been the recipient of the Society of Automotive Engineers' (SAE's) Award for Excellence in Oral Presentation and has earned the SAE Distinguished Speaker Plaque, as well. Dr. Ginsberg serves on the Editorial Board of Computing Systems in Engineering and on the Cray Research, Inc., Fortran Advisory Board. He has also been a Distinguished National Lecturer for the American Society of Mechanical Engineers, the Society for Industrial and Applied Mathematics, and the Association for Computing Machinery .
The use of supercomputers at General Motors Corporation (GM) began in the GM Research Laboratories (GMR) and has continued there, spreading to GM Divisions and Staffs, as well. Topics covered in this paper include a review of the computing environment at GM, a brief history of GM supercomputing, worldwide automotive use of supercomputers, primary GM applications, long-term benefits, and the challenges for the future.
In this paper, we will review the computing environment at GM, give a brief history of corporate supercomputing, indicate worldwide automotive utilization of supercomputers, list primary applications, describe the long-term benefits, and discuss the needs and challenges for the future.
People and the Machine Environment
Supercomputing activities at GM have been focused primarily on projects in GMR and/or cooperative activities between GMR and one or more GM Divisions or Staffs.
There are approximately 900 GMR employees, with about 50 per cent of these being R&D professionals. In this latter group, 79 per cent have a Ph.D., 18 per cent an M.S., and 3 per cent a B.S. as their highest degree. In addition, there are Electronic Data Systems (EDS) personnel serving in support roles throughout GM.
General Motors was the first automotive company to obtain its own in-house Cray Research supercomputer, which was a CRAY 1S/2300 delivered to GMR in late 1983. Today, GM has a CRAY Y-MP4/364 at GMR, a CRAY Y-MP4/232 at an EDS center in Auburn Hills, Michigan, and a CRAY X-MP/18 at Adam Opel in Germany. Throughout GM, there is a proliferation of smaller machines, including a CONVEX Computer Corporation C-210 minisuper at B-O-C Flint, Michigan, IBM mainframes, Digital Equipment Corporation (DEC) minis, a Stardent 2000 graphics super at C-P-C Engineering, numerous Silicon Graphics high-end workstations, and a large collection of workstations from IBM, Sun Microsystems, Inc., Apollo (Hewlett-Packard), and DEC. There is extensive networking among most of the machines to promote access across GM sites.
History of Supercomputing at GM
Table 1 summarizes GM's involvement with supercomputers. In 1968, GMR entered into a joint effort with Control Data Corporation (CDC) to explore the potential use of the STAR-100 to support graphics consoles. A prototype of that machine, the STAR 1-B, was installed at GMR. This project was terminated in 1972.
GM next started looking at supercomputers in late 1979. At that time the GM computing environment was dominated by several IBM mainframes (IBM 3033). Scientists and engineers developed an intuitive feel with respect to sizing their programs. They were aware that if they exceeded certain combinations of memory size and CPU time, then their job would not be completed the same day. They tried to stay within those bounds, but that became extremely difficult to do as the physical problems being considered grew increasingly complex and as they sought to develop two- and three-dimensional models.
In 1981, benchmarks were gathered both from GMR and GM Staffs and Divisions for testing on the CRAY-1 and on the CDC CYBER 205. These benchmarks included representative current and anticipated future work that would require very-large-scale computations. The results indicated that the CRAY-1 would best satisfy our needs. To get initial experience of our employees on that machine, we began to use a CRAY-1 at Boeing Computer Services and tried to ramp up our usage until such time as we could economically utilize our own in-house CRAY. Finally, in late 1983, a CRAY-1S/2300 was delivered to GMR and was in general use in early 1984. The utilization of that machine steadily grew until it was replaced by a CRAY X-MP/24 in 1986, and then that machine was replaced by a two-processor CRAY Y-MP in late 1989, with an additional CPU upgrade in early 1991. Other Cray supercomputers at GM were introduced at Adam Opel in 1985 and at EDS in 1991.
Automotive Industry Interest in Supercomputers
At about the same time GM acquired its own Cray supercomputer in late 1983, Chrysler obtained a CDC CYBER 205 supercomputer. Then in early 1985, Ford obtained a CRAY X-MP/11. As of late 1991, there were approximately 25 Cray supercomputers worldwide in automotive companies in addition to several nonautomotive Crays used by auto companies.
Figure 1 portrays an interesting trend in the growth of supercomputers within the worldwide automotive community. It depicts the number of Cray CPUs (not machines), including both X-MP and Y-MP processors, in the U.S., Europe, and the Far East in 1985, 1988, and 1991. In 1985, no automotive Cray CPUs existed in the Far East, and only two were in use in the U.S. (GM and Ford). In sharp contrast, at the end of 1991, there were 26 Cray CPUs (13 machines) in the Far East, compared with a total of 14 (four machines) in all U.S. auto companies! The specific breakdown by machines is given in Table 2; the ranking used is approximately by total CPU computational power and memory. We note that the Far East, specifically Japanese, auto companies occupy five of the top 10 positions. Their dominance would be even more obvious in Figure 1 if Japanese supercomputer CPUs were included; several of the Far East auto companies own or have access to one or more such machines in addition to their Crays.
It is interesting to note that once the first supercomputer was delivered to the automotive industry in late 1983, just about every major car company in the world began to acquire one or more such machines for in-house use within the following eight years, as evidenced by Figure 1 and Table 2.
One of the reasons for the initial delay to introduce supercomputers in the auto industry was a significant economic downturn in the early 1980s, combined with the high cost of supercomputers at that time ($5 million to $10 million range). There was also a reluctance to acquire a machine that might not be filled to capacity for quite a while after acquisition. Nevertheless, U.S., European, and the Far East auto companies began experimenting with supercomputers at service bureaus during the early 1980s.
The early acquisition of supercomputers by U.S. government labs, such as Los Alamos and Livermore, helped to spearhead the future use of supercomputers by auto companies, as well as by other businesses in private industry. The experience gained with adapting programs to
supercomputers was reported in the open literature, as well as at professional meetings where people from the automotive industry could interact with personnel from the national laboratories. Furthermore, many of the programs developed at those labs became available in the public domain. Also, some joint cooperative projects began to develop between the national labs and U.S. auto companies.
Table 3 summarizes many of the supercomputer applications currently running at GM.
Most of the supercomputer applications represent finite element or finite difference two- or three-dimensional mathematical models of physical phenomena. Both early and current applications at GM have been dominated by work in the aerodynamics area (computational fluid dynamics), combustion modeling, and structural analysis (including crashworthiness analysis); see, for example, Hammond (1985), Meintjes
(1986), Grubbs (1985), Haworth and El Tahry (1990), Haworth et al. (1990), El Tahry and Haworth (1991), Ginsberg (1988, 1989), Ginsberg and Johnson (1989), Ginsberg and Katnik (1990), Johnson and Skynar (1989), Khalil and Vander Lugt (1989), and Shkolnikov et al. (1989). This work involves both software developed in-house (primarily by GMR personnel) and use of commercial packages (used primarily by personnel in GM Divisions and Staffs). Within the past several years, additional applications have utilized the GMR supercomputer; see, for example, sheet-metal-forming applications as discussed by Chen (May 1991, July 1991), Chen and Waugh (1990), and Stoughton and Arlinghaus (1990). A most recent application by the newly formed Saturn Corporation is using the GMR Cray and simulation software to design strategically placed "crush zones" to help dissipate the energy of a crash before it reaches vehicle occupants (General Motors Corporation 1991).
In addition to the use of the Cray supercomputer, GMR scientists and engineers have been experimenting with other high-performance computers, such as hypercube and transputer-based architectures. Such machines provide a low-cost, distributed parallel computing facility. Recent work in this area on such machines includes that described by Baum and McMillan (1988, 1989), Malone (1988, 1989, 1990), Malone and Johnson (1991a, 1991b), and Morgan and Watson (1986, 1987). A more complete list of GM applications of high-performance computers is given by Ginsberg (1991).
There are several factors that justify the use of supercomputers for automotive applications. For example, the speed of such machines makes it possible to perform parameter studies early in the design cycle, when there is only a computer representation of the vehicle, and even a physical prototype may not yet exist; at that stage, a scientist or engineer can ask "what if" questions to try to observe what happens to the design as specific parameters or combination of parameters are changed. Such observations lead to discarding certain design approaches and adopting others, depending upon the results of the computer simulations. This can reduce the amount of physical prototyping that has to be done and can lead to significant improvements in quality of the final product. Other long-term benefits include improved product safety via crashworthiness modeling and greater fuel economy via aerodynamics simulations.
Accurate computer simulations have the potential to save money by reducing both the number of physical experiments that need to be
performed and the time to prepare for the physical testing. For example, in the crashworthiness area, each physical crash involves a custom, handmade car that can only be used once and may take several months to build. Furthermore, the typical auto industry cost of performing one such physical crash on a prototype vehicle can be upwards of $750,000 to $1,000,000 per test! It thus becomes apparent that realistic computer simulations have the potential to produce substantial cost savings.
The successful application of supercomputers in all phases of car design and manufacturing can hopefully lead to significant reductions in the lead time necessary to bring a new product to market. The use of supercomputers in the auto industry is still in its infancy. Creative scientists and engineers are just beginning to explore the possibilities for future automotive applications.
Needs and Challenges
Los Alamos National Laboratory received its first Cray in 1976, but the American automotive community did not begin acquiring in-house supercomputers until over seven years later. The American automobile industry needs more immediate access to new supercomputer technologies in order to rapidly utilize such machines for its specific applications. This will require growth in cooperative efforts with both government laboratories and universities to explore new architectures, to create highly efficient computational algorithms for such architectures, and to develop the necessary software support tools.
Another challenge for the future is in the networking area. Supercomputers must be able to communicate with a diverse collection of computer resources, including other supercomputers, and this requires very high bandwidth communication networks, particularly if visualization systems are to be developed that allow real-time interaction with supercomputer simulations.
The demand for faster and more realistic simulations is already pushing the capabilities of even the most sophisticated uniprocessor architectures. Thus, we must increase our investigation of parallel architectures and algorithms. We must assess the tradeoffs in using supercomputers, minisupers, and graphics supers. We must determine where massively parallel machines are appropriate. We must be able to develop hybrid approaches where portions of large problems are assigned to a variety of architectures, depending upon which machine is the most efficient for dealing with a specific section of computation. This again requires cooperative efforts among private industry, government labs,
and universities; commercial tools must be developed to assist scientists and engineers in producing highly efficient parallel programs with a minimal amount of user effort.
Realistic simulations demand visualization rather than stacks of computer paper. Making videos should become routine for scientists and engineers; it should not be necessary for such persons to become graphics experts to produce high-quality, realistic videos. In the automotive industry, videos are being produced, particularly in the crashworthiness (both side-impact and frontal-barrier simulations) and aerodynamics areas.
The challenges above are not unique to the auto industry alone. Rapid U.S. solutions to these needs could help the American automotive industry to increase its competitiveness in the world marketplace.
A. M. Baum and D. J. McMillan, "Message Passing in Parallel Real-Time Continuous System Simulations," General Motors Research Laboratories publication GMR-6146, Warren, Michigan (January 27, 1988).
A. M. Baum and D. J. McMillan, "Automated Parallelization of Serial Simulations for Hypercube Parallel Processors," in Proceedings, Eastern Multiconference on Distributed Simulation , Society for Computer Simulation, San Diego, California, pp. 131-136 (1989).
K. K. Chen, "Analysis of Binder Wrap Forming with Punch-Blank Contact," General Motors Research Laboratories publication GMR-7330, Warren, Michigan (May 1991).
K. K. Chen, "A Calculation Method for Binder Wrap with Punch Blank Contact," General Motors Research Laboratories publication GMR-7410, Warren, Michigan (July 1991).
K. K. Chen and T. G. Waugh, "Application of a Binder Wrap Calculation Model to Layout of Autobody Sheet Steel Stamping Dies," Society of Automotive Engineers paper 900278, Warrendale, Pennsylvania (1990).
S. H. El Tahry and D. C. Haworth, "A Critical Review of Turbulence Models for Applications in the Automotive Industry," American Institute of Aeronautics and Astronautics paper 91-0516, Washington, DC (January 1991).
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D. C. Hammond Jr., "Use of a Supercomputer in Aerodynamics Computations at General Motors Research Laboratories," in Supercomputers in the Automotive Industry , M. Ginsberg, Ed., special publication SP-624, Society of Automotive Engineers, Warrendale, Pennsylvania, pp. 45-51 (July 1985).
D. C. Haworth and S. H. El Tahry, "A PDF Approach for Multidimensional Turbulent Flow Calculations with Application to In-Cylinder Flows in Reciprocating Engines," General Motors Research Laboratories publication GMR-6844, Warren, Michigan (1990).
D. C. Haworth, S. H. El Tahry, M. S. Huebler, and S. Chang, "Multidimensional Port-and-Cylinder Flow Calculations for Two- and Four-Valveper-Cylinder Engines: Influence of Intake Configuration on Flow Structure," Society of Automotive Engineers paper 900257, Warrendale, Pennsylvania (February 1990).
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J. G. Malone and N. L. Johnson, "A Parallel Finite Element Contact/Impact Algorithm for Nonlinear Explicit Transient Analysis: Part I, The Search Algorithm and Contact Mechanics," General Motors Research Laboratories publication GMR-7478, Warren, Michigan (1991a).
J. G. Malone and N. L. Johnson, "A Parallel Finite Element Contact/Impact Algorithm for Nonlinear Explicit Transient Analysis: Part II, Parallel Implementation," General Motors Research Laboratories publication GMR-7479, Warren, Michigan (1991b).
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T. Stoughton and F. J. Arlinghaus, "Sheet Metal Forming Simulation Using Finite Elements," Cray Channels12 (1), 6-11 (1990).