target exascale obstacles
Posted August 6, 2014
Big data, big analytic problems, and big computers and their components create gigantic tests for tomorrow’s computer science research. To handle those challenges, three 2014 Department of Energy Early Career Award recipients are going through, around and beyond those impediments.
Today’s petascale computers can perform on the order of a quadrillion operations – 1015 – per second. To enable exascale machines, which will be a thousand times faster, computer scientists must conquer many software obstacles, developing elaborate programs that maximize the added power. Exascale architectures are expected to have complex memory systems, networks and accelerator technologies.
Applications that run on high-performance computing (HPC) systems also are growing more convoluted, and performance often depends on the input data. Changing an application to make the best use of a machine can require painstaking modifications.
At the Center for Applied Scientific Computing at Lawrence Livermore National Laboratory in California, computer scientist Todd Gamblin works on automating the fine-tuning of applications for HPC. His research, he says, “explores ways to build machine-learning techniques that predict the causes of performance problems and how to improve them.”
Statistical models, Gamblin says, can predict a program’s performance even when the input data change. But those modeling techniques must be easy to use if application developers and HPC experts are to adopt them. The payoff: faster and easier code optimization on even the most advanced computers.
Technology to do this automatically, though, must factor in many elements, including how an application uses different parts of the processor chip, memory and network – behavior that can differ within the same computer. “A program spread over a giant machine may behave differently in one core than another, and we need to understand why,” Gamblin says. For instance, what part of a program “depends on application physics? What part is completely dependent on the hardware?”