"We are rather confident," said Hirao, arguing that Japan has the technology and the people to achieve the goal.
Jack Dongarra, a professor of computer science at the University of Tennessee and one of the academic leaders of the Top 500 supercomputing list, said Japan is serious and on target to deliver a system by 2020. Citing Japan's previous accomplishments in supercomputing, Dongarra said that "when the Japanese put down a plan to deliver a machine, they deliver the machine."
Separately, Dongarra does not believe that China has a head-start on the U.S.
"They are not ahead in terms of software, they are not ahead in terms of applications," said Dongarra. But he said China has shown a willingness to invest in HPC, "where we haven't seen that same level in the U.S. at this point."
Exascale computing isn't seen as just a performance goal. A nation's system can be designed to run a wide range of scientific applications, although there are often concerns that if it takes too much power to run, it might not be financially viable.
There is, nonetheless, a clear sense that HPC is at an exciting juncture, because new technologies are needed to achieve exascale. DRAM, for instance, is too slow and too expensive to support exascale, which is one million trillion calculations per second, or 1,000 times faster than the single petaflop systems available today. Among the possibilities is phase-change memory, which has 100 times the performance of flash memory products.
Developing those new technologies will require major research investments by governments. The gridlock in Congress is partially to blame for the absence of major exascale funding, something that's at least on par with Europe. But political gridlock isn't wholly to blame. The White House's recent emphasis on big data is seen by some as delivering mixed messages about U.S. focus. The Department of Energy (DOE) has yet to offer up a clear exascale delivery date, simply describing the goal more generally as "in the 2020 timeframe."
A major constraint is the cost of power. Roughly, 1 megawatt a year costs $1 million. While the DOE has set a goal of building an exascale system that uses 20 megawatts or less, Joseph said that may be too stringent a goal. Instead, he envisioned 50-to-100-megawatt data centers built to support large-scale systems.
Dongarra and others remain optimistic that Congress will deliver on funding. There is clear bipartisan support. In the U.S. House, Rep. Randy Hultgren (R-Ill) has been working to get funding passed, and has 18 co-sponsors from both parties. Similar efforts are under way in the Senate.
Global exascale competition isn't necessarily about the basic science or the programming.
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