Future trends in HPC, part 1

As we near the end of 2011, we take a moment to reflect on the past year. It’s been a busy year for IT across virtually all verticals, from mobile and search to enterprise servers and cloud computing. When we attended HPC360 a few weeks ago, we had the pleasure to attend a keynote presentation by Addison Snell, CEO of Intersect Research in which he discussed the most important trends in high performance computing (HPC).

HPC is an exciting and growing industry that ICC has been moving into the past couple years. The traditional HPC space revolved around high-end research facilities particularly in science and engineering. However, with each year technological innovations and tailored systems such as our Supermicro GPU Simcluster have brought the realm of HPC closer to reality for many small/medium-sized business and organizations.

In this 2-part series we will look at the top 10 future trends in HPC from Intersect360′s research, coupled with our own analysis and thoughts. No better way for us computer nerds to close the year right? Let’s get started.

Top 10 HPC Trends for 2012 and Beyond

Future Trends for High Performance Computing Image

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HPC360 Conference Recap

HPC360 Flyer

We just returned from R Systems HPC360, a conference on high performance computing down in Champaign, Illinois which brought together leading industry professionals, academics, scientists, and enthusiasts.

The conference was titled HPC360 “Innovation through Modeling and Simulation”. The event took place at the i Hotel and Conference Center in Champaign, hosted by R Systems and sponsored by a number of companies including Dell, AMD, Intel, and yours truly, ICC!

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ICC releases NVIDIA powered Tesla GPU SimCluster

Last month we announced our new line of GPU supercomputing products powered by NVIDIA. These recent releases were only the build up to the real GPU highlight coming out – ICC NovaServ™ Tesla GPU SimCluster solutions.

Integrating cutting-edge technology from our industry-leading partners, ICC’s NovaServ™ Tesla GPU SimClusters are ready-to-deploy cluster solutions off the shelf, delivering the power of CPU-GPU parallel processing. The 1U 6016GT-T is a powerful stand-alone system. But the real power in high performance computing and GPU supercomputing comes from the ability to scale upward through computer clusters. By transforming the base 6016GT-T into such a configuration you gain an asset with incredible performance potential that draws upon the combined AND clustered power of CPU and GPU.

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New GPU Solutions for Grid Computing and other Supercomputing Needs

We’ve just launched two new GPU products, along with our new GPU supercomputing solutions section! GPU computing is the use of a graphics processing unit (GPU) in computing purposes, from general-purpose to supercomputing tasks. With a constantly increasing demand for greater computing performance across the board, supercomputing is more and more drawing upon a hybrid model which integrates the roles of GPUs and CPUs.

If you are looking to gain a performance boost in your cluster or grid computing, ICC’s GPU solutions may be the perfect fit. The scalability requirements involved especially in grid computing make GPU solutions an ideal IT asset.

At ICC, we integrate our top technology with NVIDIA’s® CUDA™ GPU architecture, the simplest way for you to purchase, utilize, and manage a GPU-based cluster. GPU supercomputing has never been easier than with ICC NovaServ™ solutions, providing optimal value by minimizing time spent dealing with the technology and allowing you to focus on what you do best.

Grid Computing and other GPU Supercomputing Solutions from ICC

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Graph 500, Green500, HPCC, and SPEC: Alternative benchmarks for high-performance computing

Image of Supermicro SuperRackSupercomputers have become a vital part of almost any innovative project undertaken by collaborative teams in the developed world. Server clusters can be found anywhere from the offices of small businesses to compartments in U.S. Navy submarines.

So which are the fastest supercomputers on earth? The usual measurement for high-performance computer (HPC) clusters is the TOP500 ranking, which is based on the High Performance LINPACK (HPL) benchmark. LINPACK stands for “linear equations software package”, and the benchmark measures how fast a supercomputer can solve a system of linear equations. The results are reported in units of billions of floating point operations per second (GFLOPS).

The high-performance LINPACK metric has long been the established standard for measuring computing performance, with intense competition worldwide for the lead spot in the TOP500. But some scientists criticize the TOP500 ranking for creating an incomplete picture of how to measure performance. The risk, as Mark Anderson describes in an article in IEEE Spectrum magazine, is motivating computer hardware manufacturers to develop less-effective technologies.

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GPU workstation sale (and other news)

Image of Supermicro workstationWow, this is the first update in a while on the ICC blog. We have been working on several web-based projects that have been keeping us busy, and I would like to highlight some of them (and other news) in this post.

Website and product news

First of all, as you may have noticed, our HPC by ICC section of the site launched earlier this month which describes ICC solutions for high-performance computing clusters. There is an outline of the Platform Computing HPC Suite, an industry-leading cluster management software package, as well as a diagram which explains common cluster components. Our goal is to open up high-performance computing to industries that have been slow to adopt it, even though HPC may save them a lot of money in the long term and help them stay competitive. If you think you could benefit from an upgrade to your IT infrastructure, feel free to contact us for a free consultation.

At SC10, Supermicro unveiled their GPU SuperBlade server modules (SBI-7126TG) that will offer perhaps the highest density CPU-GPU computing power available on the market. A 42U rack, comprised of six 7U blade enclosures – each with ten GPU SuperBlade modules – can carry 120 CPUs and 120 GPUs. For comparison, a rack with 42 standard dual-processor 1U servers would have 84 CPUs and no GPUs. We will have these high-density server products available on our site soon after they are released. Read more about them in the Supermicro press release or on this podcast interview with Tau Leng, GM of Supermicro, by insideHPC.

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China builds the world’s fastest supercomputer

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.

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Einstein@Home volunteers discover rare star

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.

Software Driven Networking: Enabling New Internet Speed Protocols

Internet map Photo courtesy of Matt Britt (http://en.wikipedia.org/wiki/User:Matt_Britt) and is under CC license.

A team from the Korea Advanced Institute of Science and Technology created a router, built from parts found in most high-end desktop computers, that transmits data at nearly 40 GBps.

The technique used by the scientists could lead to the development of cheap commodity chips, replacing the custom made hardware in high performance routers. The software could lead to the development of new techniques and protocols to replace the decades old infrastructure, on which the Internet currently runs.

Routers use custom hardware to route traffic between networks. Software routers use software to perform the same function. Most commercial software products can only achieve speeds of 3GB, far below the 10Gbps of common hardware. The Korean researchers developed a program called Packetshader which uses GPUs to process data packets at nearly 40GBps.

Routers manipulate data packets in myriad ways and this “parallel” processing is where the GPU really shines. Able to handle multiple data packets at once, such as encryption and authentication, it allows the CPU to perform serial operations on the data, such as packet processing to detect network breach attempts.

Gianluca Iannaccone, an engineer at Intel Labs Berkeley familiar with the software, says it could reduce the number of physical machines needed to comprise a Terabit-per-second software router, to one-third of what his research has previously indicated would be required.

“One Terabit is the entry point for enterprise-grade routers–the routers in the core of the Internet,” says Iannaccone. If enough 40Gb software routers are connected, you create a 1TB router. These clusters could one day form routers made up entirely of software.

“We can expect killer apps out of this,” added KyoungSoo Park, who was also involved. “You can build an interesting packet- or network-management system on top of a PC-based software router that can’t be implemented with a hardware router. Ultimately, you can experiment with new protocols that are not used in today’s Internet.”

Used in combination with technology like Openflow, we could develop scalable, energy-efficient data networks to replace  our current infrastructure.

Probability processing: moving beyond the 0s and 1s

For the past few years, processing technology has been steadily trying to break out of the typical x86 CPU mold that has been the standard since the 1970s. Since GPUs (graphics processing units) have emerged, traditional processing methods have been augmented with the vector computing approach of those units working in conjunction with CPUs.

Now, new types of processors are being developed that will take computing even further. As HPCWire reports, a company called Lyric Semiconductor is launching a line of products that will tackle computation in an entirely different way than the current linear method with Boolean gates that standard x86 processors employ. In other words, Lyric Semiconductor is chucking the 0s and 1s, the fundamentals of computer programming for the past half-century, out the window.

The method Lyric has been developing is based on probability processing. Michael Feldman of HPCWire describes how current computing applications have outgrown the linear model:

The goal is to construct hardware circuitry and software purpose-built for probability applications. With conventional digital technology, processing has to follow a strictly linear path. This is fine for software like operating systems, spreadsheets, word processing, and database transactions, where the computing consists of straightforward calculations or data movement. “But most of the interesting things happening nowadays don’t really fit into that model,” says Reynolds. . .That encompasses a wide range of applications including Web searching, financial modeling, genome sequence analysis, speech recognition, climate modeling, credit fraud detection, spam filtering, and financial modeling, among many others. People tend to associate these probability-based applications with human-like intelligence, and this is clearly where software, in general, is moving.

Lyric is ambitious, and this new form of processing could eventually overtake traditional CPUs in supercomputing applications. As the above article describes, new computing languages are being written that are customized for probability processing. As computers are programmed to think more and more like humans, the hardware that goes into them will continue to evolve beyond the linear modes of x86 computing.