Details of the massive VisIt run announced a while back, are starting to come out, and while they still aren’t publishing any concrete details, you can find some interesting details about the systems and testing procedures used:
The VACET team ran the experiments in April and May on six world-class supercomputers (latest TOP500 rankings noted):
• Franklin — a 38,128-core Cray XT4 located at the National Energy Research Scientific Computing Center (NERSC) at Berkeley Lab (No. 11)
• JaguarPF — a 149,504-core Cray XT5 at the Oak Ridge Leadership Computing Facility at ORNL (No. 2)
• Ranger — a 62,976-core x86_64 Linux system at the Texas Advanced Computing Center at the University of Texas at Austin (No. 8 )
• Purple — a 12,288-core IBM Power5 at LLNL (No. 50)
• Juno — an 18,432-core x86_64 Linux system at LLNL (No. 19)
• Dawn — a 147,456-core BlueGene/P system at LLNL (No. 9)
One thing I quickly noticed from this list: Nothing from SGI. (I would say Nothing from SUN as well, but I think the Ranger system is SUN). But, aside from “because we can”, why did they do this? First is the following claim from Wes Bethel:
“The results show that visualization research and development efforts have produced technology that is today capable of ingesting and processing tomorrow’s datasets,” said Berkeley Lab’s E. Wes Bethel, who is co-leader of VACET. “These results are the largest-ever problem sizes and the largest degree of concurrency ever attempted within the DOE visualization research community.”
But more to the point is this:
Another purpose of these runs was to prepare for establishing VisIt’s credentials as a “Joule code,” or a code that has demonstrated scalability at a large number of cores. DOE’s Office of Advanced Scientific Computing Research (ASCR) is establishing a set of such codes to serve as a metric for tracking code performance and scalability as supercomputers are built with tens and hundreds of thousands of processor cores. VisIt is the first and only visual data analysis code that is part of the ASCR Joule metric.
via Smashing the Trillion Zone Barrier.
PS: The comment about “nothing from SGI” is meant as a bash against SGI, as in the DoE knows better than to run any SGI’s, not a bash against the credibility of the test.
