The supercomputer built by Virginia Polytechnic Institute last year clocked a benchmark speed at a whopping 10 trillion floating operations per second, but this year it's a no-show. The supercomputer, made up of 1,100 dual-processor Apple Computer G5 systems, was disassembled shortly after.
Surely a supercomputer that's capable of computing 10 teraflops must have actually done something productive? Considering the short time the system was in operation, it's hard to tell whether it ran anything productive or just a benchmark test to get on a list.
I'm all for the need to demonstrate new technologies and also to understand why Congress wants the United States to have a faster computer than Japan--theirs is currently "bigger than ours." But the general emphasis on raw speed rather than productivity has a more negative effect on both the advancement of high-performance computing systems and the people who use them.
What does productivity mean when it comes to high-performance computing? It's the ratio of the number of jobs the system will run in 24 hours, or one week, or one month--or most importantly, how many jobs the system will run in its lifetime--over the total amount of resources that go into buying and running the system.
Basing decisions on this definition of productivity avoids the embarrassment of procuring "cheap" piles of hardware that never quite run your applications and end up cluttering your data center floor. Instead of procuring fast, expensive systems solely for the purpose of winning bragging rights, the focus shifts to producing meaningful computing output given limited resources--exactly where it needs to be.
Many high-performance computing systems are like the
Concorde--very fast and very exciting, but not productive.
This obsession with speed can also hold back the pace of research and scientific advancement. Supercomputing productivity determines when new pharmaceuticals are released, the accuracy of weather forecasts and even our national security. When the focus is taken off productivity, and computing speed becomes the main objective, the quality and quantity of research and development is compromised.
Compare the experience of the Concorde with that of JetBlue Airways. The Concorde, a tremendous technological achievement, was faster than any passenger-class airplane ever deployed. Whisking passengers back and forth across the Atlantic in two hours, the supersonic airplane promised to revolutionize air travel. But the Concorde was based on the assumption that faster must be better.
Then consider JetBlue, which does not tout itself as the fastest airline in the sky. Instead, the airlinerand efficiency by offering "red eye" flights to enable a portion of its fleet to remain productive through the night. JetBlue also schedules minimum ground time to avoid unnecessary time spent at airport gates. Quick, efficient airport turnarounds increase the number of daily flights per aircraft.
The productivity numbers speak for themselves. Last year, JetBlue served 9 million passengers and completed 67,000 flights. In its lifetime, the Concorde only served 2.5 million customers and completed fewer than 50,000 flights. The Concorde eventually failed, while JetBlue flew as an outstanding success in a largely battered industry.
Many high-performance computing systems are like the Concorde--very fast and very exciting, but not productive. Other high-performance computing systems are more similar to JetBlue, focusing on productivity and costs to yield an impressive return on investment.
For high-performance computing systems, faster isn't always better or more important. The focus needs to be on the production of systems that aren't only fast but actually get you somewhere.