Net neutrality debate goes wireless

money.cnn.com/blogs/browser/index.html

The debate over Net Neutrality, which got so heated over the summer then faded as Washington turned to the mid-term elections, is back in the news. (Net Neutrality proponents would like to see rules prohibiting phone and cable companies from limiting or prioritizing Internet traffic on their networks.) Direct Democracy has a post (third item) on Net Neutrality legislation being introduced in states such as Maryland and Maine.

And earlier this month, Net Neutrality pin-up Tim Wu issued a new paper on the idea of wireless net neutrality, which the Washington Post sums up nicely.

Proponents of wireless net neutrality wonder why wireless service and devices have to be sold together in the U.S. With wired networks, you can buy any old phone from Radioshack (RSH) or Target (TGT) and plug it into your wall jack. Why can't you do the same with your wireless device?

Part of the reason has to do with networks - the U.S. operates on two different wireless standards, so a phone that works with T-Mobile service simply isn't compatible with the Verizon networks. But mostly it has to do with the wireless operators' desire to control what rides on their networks. This isn't entirely unreasonable: If your Motorola (MOT), Nokia or Blackberry phone breaks, chances are you don't call the device manufacturer for customer service; you call the wireless carrier. On the other hand, as one Nokia (NOK) executive is fond of saying: "You wouldn't buy your computer from Verizon (VZ) or Comcast (CMCSK). Why would you buy your wireless phone from the phone company?"

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Intel's new superchip goes in search of software

Thought "dual core" microprocessors sounded impressive when they hit the streets a few years back? Forget about it. Intel (INTC) today introduced a chip with 80 "cores," or 80 distinct microprocessors arrayed in a microscopic grid, that collectively can churn through a trillion "floating point operations" a second. That makes it the world's first "teraflop" chip. FYI: "tera" comes from the Greek word for "monster."

OK, so this hot rod is not quite ready for prime time. It's still being shown off by the guys in lab coats. More importantly, John Markoff, among others, points out that nobody really knows how to write programs that take advantage of so many cores. It's a problem that has afflicted the world of "massively parallel" supercomputers for some time. It seems the hardware geeks are way ahead of the software types, and so Slashdotters have met today's news with a certain degree of frustration and self-flagellation. "We are doing something wrong," writes Ardor. "The human brain provides compelling evidence that massive parallelization works."

That's certainly what Intel believes, and it has been telling reporters it believes the new chip will excel at software problems involving "recognition, mining and synthesis." Not sure if all this is cool or creepy.

For the record, it's only been ten years (that's 1997) since the supercomputers first broke the teraflop barrier. The machine that did it was the ASCI Red at Sandia National Laboratories. Today's supercomputing champ is IBM's BlueGene/L, a machine capable of 280.6 teraflops. Want more? Check out The Smartest Machines on Earth....

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The smartest machines on earth
Supercomputers? How do you predict the unpredictable? Test bombs without explosions? With a very large, very expensive machine in a very cold room.
FORTUNE Magazine
By Oliver Ryan, Fortune Magazine
September 21 2006: 2:06 PM EDT

(Fortune Magazine) -- Racing to solve the world's most urgent problems - and to out do one another in global rankings - supercomputer designers have unleashed almost unimaginable power. A look inside the vast, chilled rooms where the big machines work their magic.

Forget about the America's Cup or Formula One: When it comes to high-stakes technical virtuosity with nationalistic undertones, nothing compares to the race for speed on the Top500. That's the twice-yearly ranking of the world's fastest supercomputers, compiled by a group of computer scientists in the U.S. and Germany.

When the latest results were announced in June, the top spot went to IBM's (Charts) BlueGene/L, which has won every contest since it was brought online in 2004. The machine, which cost more than $100 million and occupies a 2,500-square-foot air-conditioned room at California's Lawrence Livermore National Laboratory has a peak processing power of 367 teraflops, or 367 trillion "floating-point operations per second."

That's roughly equivalent to 75,000 personal computers hammering away at the same problem at the same time. Even the bottom dwellers on the Top500 list are impressive, clocking in at six teraflops, 1,000 times more muscle than your home PC.

"Tera" derives from the Greek for "monster." It's an apt description of BlueGene/L, a behemoth that helps manage the U.S. nuclear arsenal. It was this military application that attracted war-zone photographer Simon Norfolk, who captured the images on these pages. "I wanted to draw out the idea of a battlefield," says Norfolk, who, in more than a year of shooting, managed to talk himself and his oversized mahogany field camera in to photograph BlueGene/L and a number of other closely guarded supercomputing facilities on the Top500 list.

Norfolk's images provide a rare view of machines that, in a world of ever smaller and more personal computing, might seem to be relics. But thanks to extraordinary price-to-performance gains, supercomputer sales were up 25% in 2005, to $9.2 billion. That makes them the fastest-growing IT segment tracked by research firm IDC - and the demand is coming from both public and private sectors.

President Bush promised to double federal funding to America's biggest supercomputing projects in his 2006 State of the Union, and companies are finding new ways to use the smaller systems that are now flooding the market. "Supercomputers are about a trillion times faster than they were 30 years ago," says Alan Gara, chief Blue Gene architect at IBM. "And the cost hasn't changed that much. In other words, they are now a trillion times cheaper."

The essential skill of supercomputers boils down to a single word: simulation. Reality is data-rich-filled with systems that interact with one another in tangled feedback loops. So it's handy to have a massively parallel supercomputer around to break down tough simulation problems into many small bits and distribute the work to hundreds, even thousands, of wired-together processors.

Want to know how high the sea will rise given an increase in global temperature? Divide earth, sea, and air into billions of easy-to-model pieces and assign those pieces to your processors. Insert a disturbance, such as an assumption about greenhouse-gas emissions, and each processor will begin frantically calculating and recalculating to keep track of its own territories, even as neighboring territories are changing, somewhat like a giant, high-speed game of telephone.

Eventually - sometimes after days of that collective cacophony - a unified version of some future reality emerges. Variations on the technique can be applied to many of the world's other most pressing problems: the hunt for oil, planning for flu pandemics, even scanning for troublesome inbound asteroids.

Not all supercomputing applications are so apocalyptic. Procter & Gamble (Charts) once deployed a supercomputer to model the aerodynamics of a Pringles potato chip when it found that too many were flying off the assembly line. Car companies have long used supercomputers to design new models. And the financial services industry quietly burns teraflops to test investment strategies and balance portfolio risks.

Then, of course, there is the ultimate simulation.

Researchers in Switzerland are using a cousin of BlueGene/L, dubbed Blue Brain, to simulate the human neocortex. Like most in the field, Henry Markram, the project's leader, downplays the probability of his computer's "waking up" one day.

The human brain, he says, is perhaps a million times more powerful than today's most powerful machines. Still, Markram takes the hypothetical coolly in stride. "If it does happen," he says simply, "then we're going to be able to study consciousness very systematically."

Not only are supercomputers vital to solving the world's most intractable problems, they're also works of art. Check out more supercomputer stars in fortune.com's online photo gallery.

Read up on supercomputor here:
en.wikipedia.org/wiki/Supercomputer

"Supercomputers are used for highly calculation-intensive tasks such as problems involving quantum mechanical physics, weather forecasting, climate research (including research into global warming), molecular modeling (computing the structures and properties of chemical compounds, biological macromolecules, polymers, and crystals), physical simulations (such as simulation of airplanes in wind tunnels, simulation of the detonation of nuclear weapons, and research into nuclear fusion), cryptanalysis, and the like. Major universities, military agencies and scientific research laboratories are heavy users."


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www.hq.nasa.gov/hpcc/insig...upercom.htm

Moving HTMT data quickly enough among the PIM chips—only a billionth of a second delay is tolerable—is delegated to an optical communications network. "You cannot do it electronically. You would have millions, if not billions, of wires. And the heat would be impossible."

Designed by Coke Reed of the Institute for Defense Analyses, the optical Data Vortex network is a one-way whirlpool that dispenses with buffers. "That is completely unheard of!" Bergman said. "Our network acts like a multilane highway with no traffic lights."

At each network input node, a small laser generates ultrashort optical pulses that can travel at the speed of light. The electronic data are encoded onto the pulses and arranged as packets, which enter and leave the node through one of two ports on either side.

The high-speed optical network keeps packet routing as simple as possible. "The data has header information that tells the node to switch to one of the two output ports," said Princeton researcher Mark Arend.

Since all-optical switching with low latency is very difficult, Princeton uses electronic switches instead. A detector in each node "is how the optical and electronic components talk to each other," explained Qimin Yang, electrical engineering graduate student. "The data payload stays in the optical domain, so you can have a very high-speed network." Arend said there is nothing to prevent each optical beam from transmitting one trillion bits of data per second.

Optics also plays a role in HTMT's storage system. By using two laser beams and changing the angle of one beam thousands of times, it is possible to record data-encoded light into holograms. "It is a way to store information in three dimensions," said Demetri Psaltis, Thomas G. Myers Professor of electrical engineering, California Institute of Technology. "Other methods record information only on the surface of the media."

Three-dimensional storage means data access occurs in parallel, 100 times faster than conventional means. Such speed facilitates passing partial results to and from the DRAM units, Psaltis said, giving holographic storage a hybrid memory function. Full petabyte capability is targeted for 2007.

Pressing ahead

The HTMT project's current phase ends in June 1999. If funded, "our next step will be to design and implement a prototype testbed and integrate the technologies," Sterling said. "We expect the first prototype in 2001, a 400-gigaflops, four-processor system."

NASA, the Defense Advanced Research Projects Agency and the National Security Agency are funding the HTMT exploration to support mission-critical areas.

Building a petaflops system will require industrial partners. Most of the technology components are already being manufactured to some extent. However, Dorojevets is adamant that scaling to petaflops without government support is hopeless.

"No one else is going to invest money in this technology," he said. "We have known about superconducting circuits for 30 years, and we're still working on the first stage of the RSFQ processor design." Arnold Silver, TRW Inc.'s superconductor electronics manager, said it would cost approximately $30 million to make commercial manufacturing of petaflops-scale chips a reality. The other components would need similar amounts of funding.

Holographic storage "is a way to store information in three dimensions. Other methods record information only on the surface of the media."

Demetri Psaltis,
California Institute of Technology

Sterling estimates the total cost of a petaflops HTMT computer at $200 million in 2007, about double the cost of a 1998 semiconductor system that is only 1/1,000 as fast.