Back in June, IBM´s Sequoia allowed the U.S. to regain the top spot on the TOP500 list of the world’s fastest supercomputers. Americans still have bragging rights, but with a new titleholder.
Yesterday, the rankings site released benchmarking results showing that Supercomputer manufacturer had figured out a novel way to knock it's own computing champ from the top spot. Instead of building an entirely new machine, Titan, the newly crowned standard-bearer, is actually an upgraded reincarnation of an existing system being housed at the U.S. Department of Energy's Oak Ridge National Laboratory in Tennessee.
The project was funded by the Department of Energy, which awarded Nvidia and Cray $97 million to turn the once mighty 1.75 petaflop Jaguar XT5 into the world's fastest supercomputer. The upgrade, which took about a year, consisted of outfitting the device with 18,688 Tesla K20x GPU modules from Nvidia to work synchronously with a sophisticated array of 560,640 AMD processors. With Titan registering at a record-breaking 17.50 petaflops on the Linpack scale, Sequoia, rated at 16.32 petaflops, is now relegated to second place. For clarification, a petaflop is measured as a thousand trillion floating point operations per second.
Titan, in a way, highlights the rising importance of GPUs within the field of computing. Although they are slower than CPUs in carrying out a set of commands, graphics processors excel at breaking down calculations, enabling them to be processed simultaneously. The combination of CPUs and GPUs together boosts performance by allowing each process to be handled by the core best suited for it. For instance, Nvidia points out that, under typical circumstances, the company's GPUs account for 90 percent of Titan's workload.
The rise of Titan also means that the Department of Energy currently has five systems in the top 20, including the two fastest.
So what will the most powerful computer be used for? The state department says that they'll take full advantage of Titan's graphics processing prowess to build climate change models and to develop alternative energy sources and technologies, such as more efficient engines for cars.
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