GPGPUs, China Take the Lead in TOP500

By Michael Feldman

November 15, 2010

Today’s unveiling of the 36th TOP500 list revealed what many have suspected for weeks: China has beaten out the US for the number one spot, and GPU-powered machines have established themselves in the upper echelons of supercomputing. For the first time ever, the United States failed to dominate the top seven machines, and claims but a single system in the top four.

There are now seven petaflop supercomputers in the world. China’s new Tianhe-1A system, housed at the National Supercomputer Center in Tianjin, took top honors with a Linpack mark of 2.56 petaflops, pushing the 1.76 petaflop Jaguar supercomputer at ORNL into the number two spot. At number three was China again, with the Nebulae machine, at 1.27 petaflops. Japan’s TSUBAME 2.0 supercomputer is the 4th most powerful at 1.19 petaflops. And at number five is the 1.05 petaflop Hopper supercomputer installed at NERSC/Berkeley Lab. That last two petaflop entrants are the recently-announced Tera 100 system deployed at France’s Commissariat a l’Energie Atomique (CEA) and the older Roadrunner machine at Los Alamos.

Not only is the US getting drubbed at the top of the list, but so are CPUs. Of the top four machines, three are GPU-powered — all using NVIDIA Tesla processors, by the way. (Yes, I realize there are CPUs in those systems as well, but the vast majority of the FLOPS are provided by the graphics chips.) Of the top four, only the US-deployed Jaguar system relies entirely on CPUs.

In aggregate, there are 11 systems on the TOP500 that are being accelerated with GPUs, ten of them using NVIDIA chips and one using AMD Radeon processors. Only three of these GPU-ified machines are US-based, with the most powerful being the 100-teraflop “Edge” system installed at Lawrence Livermore.

The scarcity of top US systems and top CPU-only systems are not unrelated. Because GPUs offer much better performance per watt, it’s much easier today to build a multi-petaflop system accelerated by graphics hardware than having to rely solely on CPUs. For example, the number four TSUBAME 2.0 supercomputer, equipped with NVIDIA’s latest Tesla GPUS, consumes just 1.4 MW to attain 1.19 petaflops on Linpack, while the number five Hopper machine, employing AMD’s latest Opterons, requires 2.6 MW to deliver 1.05 petaflops. Since the performance-per-watt trajectory of graphics processor technology is much steeper than that of CPUs, it seems almost certain that GPUs will expand their presence on the top systems over the next few years.

We’re sure to see plenty of hand-wringing about the US being late to the GPU supercomputing party. The first GPU-powered multi-petaflop machine planned in the States looks to be the second phase of Keeneland. Keeneland is a joint project between Georgia Tech, the University of Tennessee and ORNL, which is being funded through the NSF. The first phase is already deployed at Georgia Tech and made the TOP500 at number 117 with a 64-teraflop Linpack mark. The second-phase machine will be equipped with more than 500 next-generation GPUs (so presumably based on NVIDIA “Keple” processors). That system should extend well into multi-petaflop territory, but will likely not be up and running until later in 2011.

One longer term trend that is now becoming rather apparent is the declining number of IBM systems and the increasing number of Cray systems in the top 100 portion of the list. IBM, who for a long time dominated this segment, had 49 machines in the top 100 in November 2005. In five years, that number has been cut to just 22 systems. Cray, on the other hand, claimed just eight systems in the top 100 in November 2005. It now has 25, which is more than any other vendor.

The trend parallels a general industry-wide move toward x86-based machines and away from every other CPU architecture. IBM’s 2005 dominance was the result of the popularity of its Blue Gene (PowerPC ASIC) and Power-based server machines. Cray, meanwhile, standardized its flagship XT and XE product lines on AMD Opterons. Although the top systems, in general, tend to be more heterogenous on the CPU side than HPC systems of lesser stature, the ubiquitous x86 is slowly squeezing out all other CPUs even for the most powerful supercomputers. But the allure of commodity chip architectures cuts both ways. As is now being made abundantly clear, the x86 will now have to share supercomputing honors with the new kid on the block — GPUs.

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