Category Archives: Future

Advanced Manufacturing Partnership (AMP) to spur innovation

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Photo of sun behind a factoryOn June 24, President Obama announced the Advanced Manufacturing Partnership (AMP) between the federal government, academia, and businesses to help stimulate the manufacturing sector of the U.S. economy. We have been following the so-called “Missing Middle” of small- to medium-sized manufacturers (SMMs) on this blog, and I’d like to describe some of the recent initiatives to engage this high-potential segment of our economy.

Speaking at Carnegie Mellon University, Obama described that AMP would allocate $500 million of federal money to help make U.S. manufacturing more competitive around the world.

Inspired by a report drafted by the President’s Council of Advisors on Science and Technology (PCAST), which found that there are market failures in the advanced manufacturing space that need to be overcome by government intervention, AMP will focus on five initiatives:

  1. Manufacturing for national security
  2. Materials science
  3. Robotics
  4. Energy efficiency
  5. Developing partnerships and consortia between government, universities, and industry Continue reading →

HPC can grow US manufacturing

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Photo of an fighter aircraft construction plant in New York, ca. 1944HPCwire recently ran a great article describing in a nutshell the potential that high-performance computing (HPC) can have in increasing the competitiveness of US manufacturing.

Despite what media coverage about the ailing manufacturing sector may lead one to believe, the US still leads the world in manufacturing output. In 2009, as Michael Feldman of HPCwire describes, the US accounted for 20% of the world’s manufacturing output and was 45% more productive in this area than China. Nevertheless, there are challenges ahead; the US is only fourth in manufacturing competitiveness worldwide according to one study.

Why is manufacturing such an important part of the US economy even though it employs only 10% of the national workforce? Feldman writes:

The real value of the US manufacturing sector is that it’s at the heart of much of the science and engineering innovation on which the remainder of the economy rests. Today US manufacturers employ more than a third of the country’s engineers and account for 60 percent of all private sector R&D. As such, it creates products that are used by the more lucrative service industries. Think, for example, of all the myriad services that are dependent on the production of computer chips and other electronic devices. Manufacturing, like agriculture before it, is a foundational activity that acts as a catalyst to other business sectors.

As we’ve been following on this blog, this great potential for reinvigorating the foundational sector of the US economy has been taken up as a cause by various organizations ranging from the federal government to the National Center for Manufacturing Sciences (NCMS) to universities to system integrators like us. Continue reading →

National Center for Supercomputing Applications turns 25

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Miles south of Chicago, amid the wind-swept flatlands of central Illinois, is the home of perhaps the world’s next fastest supercomputer. The National Center for Supercomputing Applications (NCSA) at the University of Illinois in Urbana-Champaign, which is co-developing the Blue Waters supercomputer, is today at the forefront of petascale computing. But 25 years ago, when the Center revved up its first machine, the computing world looked much different.

This article looks back at the highlights in NCSA’s 25-year history, which illustrate well how far computing technology has come in such a short span of time and the various innovations that supercomputers have made possible that we now take for granted. These highlights are based on the slideshow posted on NCSA’s website. (In the interest of full disclosure, ICC works with NCSA on the Dark Energy Survey, so we’re a little biased).

The first supercomputer at NCSA, which went operational in 1986, was a dual-processor machine that performed at about 400 megaflops. In comparison, the upcoming Blue Waters supercomputer will have 300,000 CPUs and a peak performance of 10 petaflops (that’s 25 million times faster than NCSA’s first supercomputer).

In 1998, NCSA came out with its first “cluster”, which connected 128 workstations together and was known as the NT Supercluster. This aggregation of towers looks somewhat comical today, and it wasn’t long before rack servers replaced these bulky form factors. Continue reading →

China builds the world’s fastest supercomputer

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Photo of Tianhe-1A supercomputer courtesy of NVIDIA.comAfter almost a year-long run, the Jaguar supercomputer at Oak Ridge National Laboratory in Tennessee has relinquished its title as the world’s fastest computer. This honor now belongs to the Tianhe-1A supercomputer located in the National Supercomputing Center in Tianjin, China.

Tianhe-1A is expected to officially become the leader of the TOP500.org list of the world’s fastest supercomputers sometime in mid-November. It clocked an impressive 2.507 petaflops on the LINPACK scale, which is about the sum of the performance of supercomputers #6 to #10 on the Top 500 list, according to insideHPC. Jaguar, now the second most powerful supercomputer in the world, had a peak performance of about 1.75 petaflops.

Although Tianhe-1A may re-ignite the anxiety in the West that usually accompanies news of great achievements from East Asia, this is not the first time that America or Europe had lost the #1 place on the Top 500. In 2002, Japan captured the top spot with their Earth Simulator (ES) supercomputer, which remained the world’s fastest until September of 2004 when IBM’s Blue Gene/L cluster at Argonne National Laboratory surpassed it. The quasi-geopolitical competition for computing power is far from over, but China’s ascendancy is actually one of the less interesting things about Tianhe-1A.

Tianhe-1A can potentially usher in a new era in “personal supercomputing”. It is the first leader of the Top 500 to make extensive use of GPUs (Graphics Processing Units). In fact, it is comprised of 7,168 NVIDIA Tesla M2050 GPUs and 14,336 Intel CPUs. In comparison, Jaguar has 37,376 AMD CPUs and no GPUs.

Continue reading →

HPC and the life sciences

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Connected network cablesThis week, a team from our company visited a large laboratory located in the Chicago area. IT representatives there told us how a major focus for them has been migrating their computing resources from a model of individual workgroups using separate clusters to a shared private cloud that all research teams in the facility can access for running their jobs. This shift to private clouds for getting the most out of dedicated clusters is a hot topic of conversation in the HPC world.

HPC in the Cloud recently published an article responding to a case study written by Platform Computing about the implementation of a private cloud at the Harvard Medical School. Both are worth a read if you are interested in the challenges encountered by small- and medium-sized life sciences organizations when they try to adopt HPC clusters.

HPC holds much promise for organizations such as the Harvard Medical School. With middleware such as Platform Computing (we are biased, I must admit, since this is what HPC clusters by ICC deploy as well) it is getting easier to operate an HPC cluster with hosts running different operating systems and applications. It used to be that this multiplicity of software on the same cluster would cause extensive compatibility and usability problems, but not so much anymore. End-users in the life sciences (such as medical researchers) are benefiting from computing applications that are productive and easy to use.

So Harvard Medical School, as the HPC in the Cloud article describes, has migrated from an inefficient computing model of unshared individual computers scattered across various laboratories to a centralized private cloud that can be accessed by any of those users and managed as one unit. Simplifying maintenance while maximizing accessibility to HPC resources by medical school staff is most likely going to save money and increase the pace of innovation in the long run.

While this is a hopeful case study that sheds light on how other organizations can pool their computing resources to great effect, challenges remain for spreading this model to other small- and medium-size laboratories and businesses. For one, private medical companies are heavily regulated by the government and their IT infrastructure has to incorporate many time-consuming applications to store detailed records.

HPC is becoming more affordable and easier to use, but software has to continue evolving to accommodate the particular context of each industry. Only then will the life sciences (not to mention other markets) have a truly turn-key HPC solution that can benefit labs and private companies of every size.

HPC and the Missing Middle in the Silicon Prairie

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HPC in the Cloud, a very insightful and well-written blog, published an article titled “HPC 360 Highlights Manufacturing’s Missing Middle“. There, author Nicole Hemsoth describes how a sector of the U.S. economy is losing competitiveness because companies are failing to take advantage of new computing technology.

This sector, called manufacturing’s “missing middle”, is comprised of the companies that furnish the large factories of the Midwest with the myriads of components and services that drive their production – the supply chain. Recent research has shown that, while China is taking full advantage of HPC technology to drive business, American industry has lagged behind, hurting its competitiveness in the global market.

There are several reasons why HPC solutions are not finding their way to the missing middle. First, most of the HPC providers in the US are located on the coasts, and their efforts are geared towards servicing clients there. Second, many companies in the missing middle are not knowledgeable about how HPC can help their business – supercomputing has long been exclusively for expensive government-funded laboratories, but that is not the case anymore. Finally, computing companies in the Midwest – the “Silicon Prairie” – have not stepped up to facilitate the missing middle’s transition into adopting supercomputing applications for business.

The moral of the story is that for many American industries to stay competitive (especially the missing middle of manufacturing), they have to incorporate HPC solutions when their business can benefit from them. It is both the responsibility of the HPC providers in the Silicon Prairie and the companies of the missing middle in the Midwest to work together in upgrading the computing technology that powers American manufacturing.

Worldwide race heats up for HPC leadership

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Planet earthAn article in Computer World by Patrick Thibodeau reports how David Turek, the vice-president of IBM, spoke last week about the growing emergence of China in the worldwide HPC competition. Turek said, “Within a year, there will be more Top500 systems in China than there are in Europe collectively.”

China currently holds the claim to having built the second-fastest supercomputer in the world. The U.S., according to the article, has 282 supercomputers in the Top500 listing, China contributes 24, and Europe has about 100. Growing their share of HPC four times over in the next year would be an impressive achievement for China.

U.S. supercomputer manufacturers, naturally, are somewhat fearful of this progress abroad. Turek, somewhat alarmed, commented, “You have sovereign nations making material investments of a tremendous magnitude to basically eat our lunch, eat our collective lunch.”

U.S. business and government are taking measures to make the United States even more competitive in the HPC market, lest that homegrown production goes the way of the U.S. automobile industry. While China is building an enormous new supercomputing center in Shenzhen, the challenge for the United States will be not only to continue leading technologically, but convincing more and more sectors of the U.S. economy that HPC solutions can grow their business beyond what their obsolete equipment now allows.

Context aware computing

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Android eyeNever drunk dial again. That is the promise from Intel CTO, Justin Rattner, as he discussed context aware computing and the next generation of personal devices, at the annual Intel Develop Forum in San Francisco.

Combining GPS technology with data from microphones, cameras, heart monitors and brain scans, new apps could track and document your every move. Don’t worry about taking a picture of that landmark; your phone already did because it knows you never remember to. It also updated your Facebook profile and checked you in on Foursquare.

If you can get past the privacy concerns, this technology may have potential.

TV that recommends what to watch, based on who is holding the remote-because it can tell who you are by the way you hold it.

Apps that suggest where to eat in your area because the phone knows you just ran  5 miles and need those 40g of protein to continue your krebs cycle and it knows nobody wants to be around you when your blood sugar drops.

Context aware devices may have their day, and in certain situations certainly have their place, but with the serious implications to privacy and the flawed security structure of the internet, the zeitgeist will need to change significantly for this technology to be accepted.

Then again, I thought American Idol was rubbish, so what do I know?

Einstein@Home volunteers discover rare star

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Image of planet earthWhen I was a freshman in college, I helped the professor of my introductory astronomy class to conduct some of his research. The job wasn’t hard: I had to look at digital maps of the sky and try to find a particular type of rare star. Open map segment, click on pixels around a light source (star), evaluate if pixels have sufficient contrast, repeat. I never found the kind of star my professor was searching for.

Looking back on this experience, my job could have easily been done by a computer program. It would probably have been magnitudes more efficient that I was at analyzing the thousands of pixels on the map, and my professor wouldn’t have had to pay it $8.50/hr. Of course, as a college freshman, I was grateful for the research experience and the cash.

These days, universities are becoming more sophisticated in the way they let amateurs help them with research. A project called Einstein@Home recently had a breakthrough when a rotating pulsar was discovered by volunteer scientists, the first such accomplishment of its kind.

As the press release by the National Science Foundation describes, Einsten@Home is a collaborative project that allows lay people to donate the computing power of their PCs and laptops to help search the sky for celestial objects that have not been discovered yet. Over a quarter of a million volunteers from almost every country on earth participate in this venture, and now it has payed off.

Some of the volunteers’ computers recently unearthed a rare star that had not been documented before. This type of star is very important to researchers studying Einstein’s general theory of relativity, one of the most complicated paradigms in science. For such a star to be formed, there are many preconditions that must occur. As the press release noted above explains:

When two massive stars are born close together from the same cloud of gas, they can form a binary system and orbit each other from birth. If those two stars are at least a few times as massive as our sun, their lives will both end in supernova explosions. The more massive star explodes first, leaving behind a neutron star. If the explosion does not kick the second star away, the binary system survives. The neutron star can now be visible as a radio pulsar, and it slowly loses energy and spins down. Later, the second star can swell up, allowing the neutron star to suck up its matter. The matter falling onto the neutron star spins it up and reduces its magnetic field. This is called “recycling” because it returns the neutron star to a quickly-spinning state. Finally, the second star also explodes in a supernova, producing another neutron star. If this second explosion also fails to disrupt the binary, a double neutron star binary is formed. Otherwise, the spun-up neutron star is left with no companion and becomes a “disrupted recycled pulsar“, spinning between a few and 50 times per second.

Quite a find! With this recent success, collaborative computing projects such as Einstein@Home, which require very little involvement on the part of the lay user, will become more and more popular. There are many such opportunities available, and the page to download BOINC, the program that allows your computer to facilitate scientific research, even has a special option for using a GPU if your computer has one. With NVIDIA releasing their new GeForce GTS 450 GPU today for just $129, beefy gaming computers can now be easily used to scan the heavens when they’re not being honed to shoot alien mutants.

I know the first thing I’m going to do when I load up my personal laptop is install Einstein@Home. If I could not find the stars I was looking for when I was in astronomy class, maybe my computer can.

Extending Moore’s Law

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ProcessorAccording to Science News, researchers at Rice University have created the first two-terminal, pure silicon memory chips, easily adaptable to nanoelectric manufacturing.

Researchers discovered that silicon oxide could replace carbon in the process. When an electric charge is sent through silicon oxide-an insulator-between semiconducting sheets of polycrystalline silicon, it forms a conductive pathway as small as 5 nanometers (billionths of a meter) wide. This process creates a two-terminal resistive switch, far smaller than current circuits in computer architectures.

By continuously breaking and connecting these nano strips, one creates robust and reliable memory bits.

“The beauty of it is its simplicity,” said Professor James Tour. That, he said, will be key to the technology’s scalability. Silicon oxide switches or memory locations require only two terminals, not three (as in flash memory), because the physical process doesn’t require the device to hold a charge.

The implications for chip manufacturers and the continuation of Moore’s Law holds the promise for this technology.