Scientists from Stanford Engineering’s Center for Turbulence Research (CTR) worked on the computational fluid dynamics (CFD) simulations utilizing Sequoia supercomputer, a supercomputer at the Lawrence Livermore National Laboratories, to understand the engine noise from supersonic jets. Computational fluid dynamics simulations required finely tuned balance of computation, memory and communication components.
It is the first time that the team of scientists has successfully pushed the CFD simulation ahead of 1 million cores.A floor view of the newly installed Sequoia supercomputer at the Lawrence Livermore National Laboratories. (Photo: Courtesy of Lawrence Livermore National Laboratories)
This test along with the others on Sequoia supercomputer, with 1.57 million processing cores, will help to understand the capabilities of the IBM BlueGene/Q computer. Although Sequoia is number two on the list of the world’s most powerful computers, but it has the maximum number of computational processing cores, according to Joseph Nichols, Research associate in the center, who is working on the computer. “It uniquely enables us to run 1M+ core simulations, to glimpse what the future has in store,” Nichols said.
“The computer allows us to test the scalability of our algorithms to large numbers of cores – if a code is scalable, the time-to-solution will keep dropping as greater numbers of cores added to the machine,” said Nichols.
The computer has also been used to simulate the air turbulence over jet wings and modelling scramjet engines.
“These runs represent at least an order-of-magnitude increase in computational power over the largest simulations performed at the Center for Turbulence Research previously,” said Nichols “The implications for predictive science are mind-boggling.”
“Computational fluid dynamics (CFD) simulations, like the one Nichols solved, are incredibly complex. Only recently, with the advent of massive supercomputers boasting hundreds of thousands of computing cores, have engineers been able to model jet engines and the noise they produce with accuracy and speed,” said Parviz Moin, the Franklin M. and Caroline P. Johnson Professor in the School of Engineering and Director of CTR.