There is almost an obsessive focus at the supercomputing conference in Seattle on reaching exascale computing, a level of computing power that is roughly 1,000 times more powerful than anything that is running today, in this decade.
In the lives of most people, something that is eight or nine years off may seem like a long time, but at SC11, it feels as if it is just around the corner. Part of the push is coming from the U.S. Department of Energy, which will fund these massive systems. The DOE told the industry this summer that it wants an exascale system delivered in the 2019-2020 timeframe that won't use more than 20 MW of power. The government has been seeking proposals about how to achieve this.
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To put 20 MW of power in perspective, consider the supercomputer that IBM is building for the DOE's Lawrence Livermore National Laboratory. This system will be capable of speeds of 20 petaflops. It will be one of the largest supercomputers in the world as well as one of the most energy efficient. But when it is completely turned on next year, it will still use somewhere in the range of 7 to 8 MW of power, according to IBM. An exascale system has the compute power of 1,000 petaflops. (A petaflop is a quadrillion floating-point operations per second.)
"We're in a power constrained world now," said Steve Scott, the CTO of Nvidia Corp.'s Telsa business, "where the performance we can get on a chip is constrained not by the number of transistors we can put on a chip, but rather by the power."
Scott sees x86 computing processing limited by its overhead processes. GPU processors, in contrast, provide throughput with very little overhead, and with less energy per operation.
Nvidia has been building HPC (high-performance computing) systems with its GPUs and CPUs, often enough, from Advanced Micro Devices. This hybrid approach is also moving toward ARM processors, widely used in cell phones, which may lead to an integrated GPU and ARM hybrid processor.
Scott believes the DOE's 20 MW goal can be achieved by 2022. But if the government's exascale program comes through with funding, it may enable Nvidia to be more aggressive in circuit and architectural techniques, making it possible to achieve that power level goal by 2019.
Scott said reaching that level of efficiency will require improving power usage by 50 times.
While 20 MW may seem like a lot of power, Scott points out that there are cloud computing facilities that require as much as 100 MW of power.