Modeling Climate at Warp Speed
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Two new NASA technologies have squeezed 10 times
more power out of climate-modeling supercomputers.
May 2, 2002:
For many people, faster computers mean better video games
and quicker Internet surfing. But for decision makers grappling
with the future of Earth's climate, faster computers have a very
practical benefit: more realistic climate simulations that give
more reliable predictions.
NASA scientists have managed to squeeze about 10 times more power out of cutting-edge "parallel" supercomputers through innovations in software and memory design. This leap in effective computing "muscle" -- together with the data from NASA's Earth-observing satellites -- enables greater realism and statistical confidence in simulations of global climate.
Above: New SGI® Origin® 3000 Series supercomputers, shown here, together with software tools developed at NASA's Ames Research Center are producing a 10-fold improvement in computing power. The computer on the right is the size of a tall filing cabinet. Image courtesy SGI.
Whether the question concerns the path of an approaching hurricane or the rise in global temperatures over the next century, predictions always carry some amount of uncertainty. But the computer "models" that produce the simulations can be improved so that this uncertainty is reduced.
Making these improvements will require all the computing power
scientists can get their hands on.
To provide the immense "number crunching" power needed for demanding scientific applications such as climate simulation, some computer makers are turning to "parallel" designs with hundreds or thousands of processors in one supercomputer.
The numbers on these machines make even the fastest desktop computers look like pocket calculators. For example, the newest supercomputer at NASA's Goddard Space Flight Center boasts 512 processors each running at 400 MHz, 128 GB of RAM, 2,800 GB of disk space, and a peak performance of 409 gigaflops! (A "gigaflop" is a billion calculations per second.) A newer machine at NASA's Ames Research Center will top even this with 1,024 processors.
Above: The bottom line shows how the increase in computing power (gigaflops) normally tapers off as the number of processors increases. The top line shows the performance on the same processors using the software tools developed by NASA. [more]
But simply adding more processors doesn't guarantee a proportionate
increase in effective power. In fact, the full potential of these
parallel supercomputers still has not been tapped.
"So what's the problem? Each node (i.e., processor) has certain performance," Asrar explains. "Individually they perform well, but as you add them all together, as the number of nodes goes up, the overall efficiency degrades." For example, a system with 100 processors would not have 100 times the power of a single processor -- the overall performance would be somewhat lower.
This loss of computing efficiency is a bit like what happens
when people must work together to get a task done. Some effort
must go into managing and coordinating the people involved --
effort that's diverted away from producing anything -- and even
the productive workers must spend some amount of time communicating
with each other. In a similar way, a supercomputer with more
processors must use more of its power to coordinate those processors,
and the increased communication between all the processors bogs
the system down.
So the challenge was, how do you write the computer programs such that you get the maximum performance out of a single machine?" Asrar says.
Left: Simulations of Earth's climate are among
the most computationally intensive problems in science. Click
on the image to view an MPG movie.
For the past four years, scientists at NASA's Ames Research Center have been working in partnership with computer maker Silicon Graphics, Inc., to tackle this problem. The fruits of their labor are two new technologies that increase the effective power of these machines by roughly an order of magnitude (that is, a factor of 10). Both technologies are freely available to the supercomputing community, are computer vendor independent, and are not specific to climate modeling.
The first of these technologies is a memory architecture called "single-image shared memory." In this design, all of the supercomputer's memory is used as one continuous memory space by all of the processors. (Other architectures distribute the memory among the processors.) This lets the processors exchange the messages needed to coordinate their efforts by accessing this "common ground" of memory. This scheme is more efficient than passing the messages directly between the processors, as most parallel supercomputers do.
Below: Using faster computers, forecasters will be able to narrow the estimated path of hurricanes and perhaps save millions of dollars in unneeded evacuations. Image courtesy NOAA.
But a new memory architecture needs software that knows how to make good use of it. The second innovation does just that. It is a software design tool called "multi-level parallelism." Software made using this tool can use the common pool of memory to break the problem being solved into both coarse-grained and fine-grained pieces, as needed, and compute these pieces in parallel. The single memory space gives more flexibility in dividing up the problem than other designs in which the memory is physically divided among the processors.
The extra computing power milked from the processors by these technologies will help NASA's Earth Science Enterprise make better models of Earth's climate.
These models work by dividing the atmosphere and oceans up
into a 3-dimensional grid of boxes. These boxes are assigned
values for temperature, moisture content, chemical content, and
so on, and then the interactions between the boxes are calculated
using equations from physics and chemistry. The result is an
approximation of the real system.
With more computing power available, more of the physics of the real climate system can be incorporated into the models, and the atmosphere can be divided into more, smaller boxes. This makes the models more realistic, and the predictions they will produce will be of more interest on a regional scale.
Also, the ability to run these models faster will mean that more simulations can be performed, which will produce a larger pool of results. In statistical terms, this larger "population" will allow for a better analysis of the strength of the conclusions.
Above: The software tools developed by NASA and SGI can be used for other simulations, too. Show here is a supercomputer model of a human protein. [more]
NASA's suite of Earth-observing satellites, together with
a global network of meteorological stations, provide the dose
of real-world data that is needed to keep the models on track.
And the archives of this data provide the ultimate proving grounds
for the models: Can the computers accurately "predict"
the real weather observed in the past?
Asrar says that the computer models are already quite good at this, but there's still room for improvement. As supercomputers continue to advance -- along with the software that taps that power -- climate models will become more and more accurate, offering better answers to the vexing questions of climate change.
New 512-processor supercomputer -- short article about the 512-processor SGI machine and some of the science applications for which it will be used
NASA Advanced Supercomputing Division -- home page, contains lots of information about the supercomputing resources at NASA and the many science and engineering challenges that make use of them.
Right: A simulated hurricane produced by the NASA/NCAR Finite Volume General Circulation Model. These false-color maps trace precipitation (mm/hr) and wind vectors ~1.5 km above the ocean surface during a 24 hour period. [more]
NASA's Earth Science Enterprise -- home page of the program at NASA that uses satellite and space technology to better understand the Earth's natural processes
Supercomputing resources at NASA -- information on NASA's major supercomputers
What is data assimilation? -- explanation and links related to the important process of merging satellite data into computer simulations of climate
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