The computer, known as Tianhe-1A, has 1.4 times the horsepower of the current top computer, which is at a national laboratory in Tennessee, as measured by the standard test used to gauge how well the systems handle mathematical calculations, said Jack Dongarra, a University of Tennessee computer scientist who maintains the official supercomputer rankings.
Although the official list of the top 500 fastest machines, which comes out every six months, is not due to be completed by Mr. Dongarra until next week, he said the Chinese computer “blows away the existing No. 1 machine.” He added, “We don’t close the books until Nov. 1, but I would say it is unlikely we will see a system that is faster.”
Tianhe-1A epitomizes modern heterogeneous computing by coupling massively parallel GPUs with multi-core CPUs, enabling significant achievements in performance, size and power. The system uses 7,168 NVIDIA® Tesla™ M2050 GPUs and 14,336 CPUs; it would require more than 50,000 CPUs and twice as much floor space to deliver the same performance using CPUs alone.
More importantly, a 2.507 petaflop system built entirely with CPUs would consume more than 12 megawatts. Thanks to the use of GPUs in a heterogeneous computing environment, Tianhe-1A consumes only 4.04 megawatts, making it 3 times more power efficient -- the difference in power consumption is enough to provide electricity to over 5000 homes for a year.
The Chinese system follows that model by linking thousands upon thousands of chips made by the American companies Intel and Nvidia. But the secret sauce behind the system — and the technological achievement — is the interconnect, or networking technology, developed by Chinese researchers that shuttles data back and forth across the smaller computers at breakneck rates, Mr. Dongarra said.
“That technology was built by them,” Mr. Dongarra said. “They are taking supercomputing very seriously and making a deep commitment.”
The Chinese interconnect can handle data at about twice the speed of a common interconnect called InfiniBand used in many supercomputers.
“What is scary about this is that the U.S. dominance in high-performance computing is at risk,” said Wu-chun Feng, a supercomputing expert and professor at Virginia Polytechnic Institute and State University. “One could argue that this hits the foundation of our economic future.”
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