GM speeds time to market through blistering fast processors: General Motors' vehicle development process gets a big boost from the latest in supercomputers

Automotive Design & Production, July, 2004 by Lawrence S. Gould

Supercomputing, what General Motors (GM; Detroit, MI) calls "high-performance computing" (HPC), is so valuable that the company will be more than doubling its supercomputing capacity by early next year. Its new supercomputers run at nine teraflops--9 trillion calculations per second, which is the equivalent of computing in one second one calculation per second for just over 285,000 years.

Impressive, yes, but one might wonder: "What's it good for?" In GM's case, a lot. Supercomputing is a crucial tool for vehicle development, from concept models at the early stages of design to more detailed models as the designs evolve. It is also one more "enabler" to global competitiveness.

THE VERY MODERN MODEL OF A SUPERCOMPUTER

This is not GM's first supercomputer. It's an upgrade to an existing system. Consider it a scheduled upgrade, given that much of GM's computing equipment is on a three-year lease. By swapping out equipment every three years, GM stays on the leading edge of computing technology and ahead of its computing needs.

GM's previous supercomputing system consisted of computers from IBM and Silicon Graphics Inc. (Mountain View, CA) combined in a four-way system. (A four-way system is one based on a microprocessor that can issue two integer and two floating-point instructions for every processor clock cycle, as opposed to just one of either.) For software, in addition to Unigraphics for computer-aided design (CAD) and product lifecycle management (PLM), the primary computer-aided engineering (CAE) analysis software at GM includes MSC-Nastran from MSC.Software Corp. (Costa Mesa, CA) for structures, LS-Dyna from Livermore Software Technology Corp. (Livermore, CA) for crash simulations, and computational fluid dynamics software from Fluent Inc. (Lebanon, NH) for aerodynamics.

GM's new HPC system consists of two models of 64-bit IBM supercomputers. The first model, the pSeries p655 1.7 GHz 8-way, based on IBM's Power4 processor, was up and running at the beginning of 2004. The Power5-based supercomputer will be delivered later this year and running in early 2005. The Power5 processors, which supersede the Power4, are "considerably faster than the Power4s," says Tom Tecco, director of CAE, CAT, and electrical systems in the IS & S Group of GM. Once everything is installed, the entire computing system will probably be about five to six times faster than what GM had, and there'll be more of it to crunch through more computer jobs.

GM will deploy these supercomputers to all of its design centers around the world. This lets the designers and engineers share the results of analysis a "little bit more easily" than if the systems were different, explains Tecco. (All the regions use the same versions of software, as well.) While analysis jobs are usually run regionally, if a shortage of capacity should occur in one region, GM can run the job on the super-computer in another region.

BUT WHAT'S IT GOOD FOR?

The single biggest application of GM's supercomputing is for crash simulation: full-frontal, offset-frontal, angle-frontal, side-impact, rear-impact, to name a few types of crashes. Crash worthiness, explains Bob Kruse, GM's executive director of Vehicle Integration for North American Engineering, "while done very early in the development process, gets validated very late in the development process--meaning, after you've already completely built the vehicle." Unlike in the aerospace industry, the government doesn't let automakers simply submit math simulations that say their vehicles meet federal motor vehicle safety standards. Instead, the automakers crash the real things. Using silicon and math to crash cars into walls is much faster and cheaper than crashing actual cars into walls. Plus, the availability of virtual cars, walls, and crashes is virtually limitless. By using the supercomputer early in vehicle development, says Kruse, "by the time we go through the time and the expense of driving a vehicle into a wall, we are pretty damn sure how it's going to perform."

[ILLUSTRATION OMITTED]

Such simulations can run at different speeds, different angles, at different vehicle load structure. "That iteration in math is a very efficient way to go," says Kruse. "The more you do, the higher the fidelity--the sophistication--of the models. The more sophisticated the models, the more parts, the more things, and the more dimensions you try to analyze." However, this means the more compute capacity you need. (Given that crash testing is the epitome of non-linear problems, read: "complex," you need a tremendous amount of computer power just to start with.)

GM has other complex non-linear problems, such as those in thermodynamics. For instance, GM simulates the airflow through the front end of a vehicle to predict thermal characteristics under the hood. Another example involves brakes, which generate lots of heat. GM simulates airflow across brake calipers and shoes to determine if a baffle needs tweaking or fins added to ensure the brakes don't overheat. Another batch of non-linear problems involves aerodynamics. More and more of these are moving from the wind tunnel to the virtual world.