IBM's Blue Gene technology has received some notable attention lately — especially internationally. Last month, Germany and Japan announced separate deployments of Blue Gene/L systems. Both deployments now represent the highest performing supercomputer systems in their respective countries. Although the timing may have been a coincidence, IBM views these events as part of a growing acceptance of Blue Gene to solve a wider range of high performance computing problems.
Simulating Quarks and Gluons
At Japan's Inter-University Research Institute Corporation High Energy Accelerator Research Organization (KEK), they have deployed ten racks of Blue Gene/L technology, configured into three separate systems, with an aggregate peak performance of 57.3 teraflops.
By breaking the Blue Gene racks up into three systems, KEK identified the three-system configuration as the best approach to perform the types of particle physics simulation calculations they have in mind. The calculations at KEK require changes in parameters for each simulation and they simultaneously run massive number of simulations with those different parameters.
KEK's use of supercomputers has allowed significant achievements in high-energy accelerator science, especially in simulating the dynamics of quarks and gluons, the elementary components of matter. KEK's research into the underlying secrets of nature, including the origin of the universe and matter, requires large-scale numerical simulation and a dramatic increase in computing power.
“As our research in the areas of theoretical high energy physics continues to evolve, the need for computing power is ever greater,” said Ph.D. Shoji Hashimoto, an associate professor, Institute of Particle and Nuclear Studies, High Energy Accelerator Research Organization. “IBM's Blue Gene is the ideal system to offer our institute performance levels that will allow areas of scientific discovery that were previously unattainable.”
Scientific Research for Europe
Meanwhile, the German Research Center Juelich, one of the three high-profile German supercomputing centers, inaugurated a newly deployed Blue Gene system as the most powerful supercomputer in Europe.
The system joins an existing 8.9 teraflop supercomputer at Research Center Juelich that is also based on IBM POWER architecture technology. This dual supercomputer system offers the capacity to fulfill the varying needs of the scientific user community. In addition to the two supercomputers, Juelich's ability to support researchers in methodology, fast algorithms and program efficiency is another important aspect of the center's infrastructure.
The Juelich Blue Gene/L installation will offer a peak performance of 45.8 teraflops and a sustained performance of 36.5 teraflops. Juelich originally had one Blue Gene rack. In this latest deployment they added seven more, connecting them together into an eight-rack system.
The Juelich installation will be used for the most compute intensive research tasks of German and European scientists. Serving as a virtual laboratory, the system will be used for scientific discovery in areas such as particle physics, material sciences, life sciences and environmental research. For example, it will be used to simulate the diffusion of harmful materials in soil and in the atmosphere.
“The request for compute time will go up by a factor of one thousand in the next five years,” predicts Prof. Joachim Treusch, chairman of the board of the Research Center Juelich. “Therefore we will extend our core competency in the area of supercomputing massively in the future.”
“The IBM Blue Gene architecture has proven to be highly attractive to researchers,” said Nurcan Rasig, director of Supercomputing Solutions at IBM in Germany. “The conception of this computer type is especially suitable for capability computing, as high performance and excellent scaling are possible. This is an important feature for getting new scientific results that cannot be reached by conventional HPC clusters.”
The Blue Gene Approach
Herb Schultz, Blue Gene General Manager at IBM, would agree with that assessment. According to him, when you look at the current technology in commodity components, it's just not practical to use them to build multi-hundred teraflop HPC systems.
“There's a physical practical limit to how big systems can get using certain types of technology, says Schultz. “You can't just put 50,000 blades together and make this big system — you don't have the space, you don't have the power, etc.”
He says that the real advantages of the Blue Gene technology is that it has very favorable price/performance and performance/watt characteristics and it was designed to scale extremely well. But to make it commercially viable it had to be built from relatively modestly priced components — PowerPC 440 processors at a conservative 700 MHz clock speed. The relatively low amount of power required for this chip allowed IBM to pack a lot of them close together. Each Blue Gene rack contains 1024 dual-processor nodes.
“It can scale very well,” says Schultz. “We went from 70 teraflops, and six months later doubled it, and then doubled it again. And if someone with enough money wanted to double it again and build a 128-rack system, they could.”
According the Schultz, beyond 128 racks, you're starting to reach the architectural limits of the current technology. But in the future, IBM intends to improve the technology so that you can get a petaflop in roughly the same footprint as the current 64-rack Blue Gene system at Lawrence Livermore National Laboratory (LLNL). IBM's R&D PERCS program, described in last week's issue of HPCwire (http://www.hpcwire.com/hpc/614724.html), is another possible avenue to reach petascale systems. But whether PERCS employs Blue Gene technology or goes in a different direction is still an open question.
Applications Catching Up
But before that happens, today's applications need to take advantage of the current level of Blue Gene technology. Developers are working hard to unleash the performance in current systems and, according to Schultz, this is starting to happen. After more than a year in commercial production, the Blue Gene ecosystem has begun to mature. Specifically, more applications are being ported to the architecture, attracting a wider range of users.
Schultz says it was the middle of last year that people were proving to themselves that the Blue Gene technology was suitable for their applications and would allow their codes to scale. This encouraged customers with one- or two-rack systems to consider scaling up their hardware.
The Blue Gene architecture was initially designed in collaboration with LLNL for their nuclear weapons analysis mission. But over the past year and a half, applications supporting astronomy (radio telescopes), fluid dynamics (large eddy simulations) and biotechnology (genomics) have been successfully ported to Blue Gene.
“Now it's easier to prove the value of Blue Gene with something other than standard benchmarks,” says Schultz. “We're getting some real code ported and run. The scaling is very good. The performance is good. So I think people are starting to see that Blue Gene is now ready for a variety of applications besides the ones it was originally designed for — high energy physics codes for national laboratories.”
Blue Genes on Wall Street?
There's also been some interest in running financial codes (Monte Carlo techniques and options pricing models) on Blue Gene. In fact, on April 24th, IBM will be pitching this idea to the financial community, at the Linux on Wall Street conference (http://www.linuxonwallstreet.com). The company will present a keynote address at the conference that describes how Blue Gene technology can be applied to financial applications. IBM would like to to encourage some involvement from the Wall Street community so that more financial codes can be ported to the architecture.
Schultz says that when Blue Gene was conceived, IBM had no thoughts that the technology would be hosting financial applications. But a lot of these customers are grappling with very compute intense applications that need to be run in data centers with limited amounts of space, power, and cooling. Blade servers are the traditional solution, but Blue Gene systems can deliver more computing performance, using less power and space. And, according to Schultz, from an end user's point of view, Blue Gene looks like a Linux cluster.
Getting Up To Speed
One thing that has stimulated Blue Gene application porting is IBM's own Deep Computing Capacity On Demand (DCCOD) Center. This has enabled users to get access to the technology without having to purchase a system — an expensive proposition, since a single Blue Gene rack costs over a million dollars!
The DCCOD center allows users to borrow Blue Gene cycles on machines owned and maintained by IBM. It has provided an avenue to the technology for two important groups: (1) ISVs, so that they can research and develop key applications for Blue Gene and (2) End users, who can trial and scale their custom applications on the technology before committing to a system purchase. Schultz believes the DCCOD Center has been invaluble in enabling developers to get experience with Blue Gene technology.
“This was one of our original challenges,” says Schultz. When you have a big system like this and the smallest thing you [sell] is 1024 nodes, how can you get people access to it? The On Demand Center gives people that access.”
Apart from the DCCOD, some users can also get access to government-owned Blue Gene systems, where the owners have been mandated to loan out some of their cycles.
An Elite Market
No matter how many applications end up on Blue Gene, it will never be a general-purpose high performance computer. Nor was it intended to be. Blue Gene inhabits the rarified atmosphere of the HPC capability market, defined by IDC as supercomputers costing over $1 million. This market has had flat or declining revenues for several years.
“I have no reason to believe that the trajectory is going to change,” says Schultz. “But I do think that Blue Gene's share of that space will get bigger.”
Schultz admits that trying to position something like Blue Gene in the marketplace is always a challenge. Why would someone want to buy this? You can talk about its scalability, its number one performance ranking, its power/cooling efficiency, etc. But those are just attributes. According to Schultz, the awareness that's starting to emerge is that it solves problems that couldn't be solved before.
“There are a lot of customers out there with really big problems that are just waiting for the solution to come along,” says Schultz. “That's our customer base — those who really want to move ahead advancing their science.”