Keeping an Eye on the Prize

Abstract

Setting performance goals is part of the business plan for almost every company. The same is true in the world of supercomputers. Ten years ago, the Department of Energy (DOE) launched the Accelerated Strategic Computing Initiative (ASCI) to help ensure the safety and reliability of the nation's nuclear weapons stockpile without nuclear testing. ASCI, which is now called the Advanced Simulation and Computing (ASC) Program and is managed by DOE's National Nuclear Security Administration (NNSA), set an initial 10-year goal to obtain computers that could process up to 100 trillion floating-point operations per second (teraflops). Many computer experts thought the goal was overly ambitious, but the program's results have proved them wrong. Last November, a Livermore-IBM team received the 2005 Gordon Bell Prize for achieving more than 100 teraflops while modeling the pressure-induced solidification of molten metal. The prestigious prize, which is named for a founding father of supercomputing, is awarded each year at the Supercomputing Conference to innovators who advance high-performance computing. Recipients for the 2005 prize included six Livermore scientists--physicists Fred Streitz, James Glosli, and Mehul Patel and computer scientists Bor Chan, Robert Yates, and Bronis de Supinski--as well as IBM researchers James Sexton and John Gunnels. This team produced the first atomic-scale model of metal solidification from the liquid phase with results that were independent of system size. The record-setting calculation used Livermore's domain decomposition molecular-dynamics (ddcMD) code running on BlueGene/L, a supercomputer developed by IBM in partnership with the ASC Program. BlueGene/L reached 280.6 teraflops on the Linpack benchmark, the industry standard used to measure computing speed. As a result, it ranks first on the list of Top500 Supercomputer Sites released in November 2005. To evaluate the performance of nuclear weapons systems, scientists must understand how materials behave under extreme conditions. Because experiments at high pressures and temperatures are often difficult or impossible to conduct, scientists rely on computer models that have been validated with obtainable data. Of particular interest to weapons scientists is the solidification of metals. ''To predict the performance of aging nuclear weapons, we need detailed information on a material's phase transitions'', says Streitz, who leads the Livermore-IBM team. For example, scientists want to know what happens to a metal as it changes from molten liquid to a solid and how that transition affects the material's characteristics, such as its strength.