Visit additional Tabor Communication Publications
July 28, 2009
LIVERMORE, Calif., July 28 -- Computer scientists at Sandia National Laboratories in Livermore, Calif., have for the first time successfully demonstrated the ability to run more than a million Linux kernels as virtual machines.
The achievement will allow cyber security researchers to more effectively observe behavior found in malicious botnets, or networks of infected machines that can operate on the scale of a million nodes. Botnets, said Sandia's Ron Minnich, are often difficult to analyze since they are geographically spread all over the world.
Sandia scientists used virtual machine (VM) technology and the power of its Thunderbird supercomputing cluster for the demonstration.
Running a high volume of VMs on one supercomputer -- at a similar scale as a botnet -- would allow cyber researchers to watch how botnets work and explore ways to stop them in their tracks. "We can get control at a level we never had before," said Minnich.
Previously, Minnich said, researchers had only been able to run up to 20,000 kernels concurrently (a "kernel" is the central component of most computer operating systems). The more kernels that can be run at once, he said, the more effective cyber security professionals can be in combating the global botnet problem. "Eventually, we would like to be able to emulate the computer network of a small nation, or even one as large as the United States, in order to 'virtualize' and monitor a cyber attack," he said.
A related use for millions to tens of millions of operating systems, Sandia's researchers suggest, is to construct high-fidelity models of parts of the Internet.
"The sheer size of the Internet makes it very difficult to understand in even a limited way," said Minnich. "Many phenomena occurring on the Internet are poorly understood, because we lack the ability to model it adequately. By running actual operating system instances to represent nodes on the Internet, we will be able not just to simulate the functioning of the Internet at the network level, but to emulate Internet functionality."
A virtual machine, originally defined by researchers Gerald J. Popek and Robert P. Goldberg as "an efficient, isolated duplicate of a real machine," is essentially a set of software programs running on one computer that, collectively, acts like a separate, complete unit. "You fire it up and it looks like a full computer," said Sandia's Don Rudish. Within the virtual machine, one can then start up an operating system kernel, so "at some point you have this little world inside the virtual machine that looks just like a full machine, running a full operating system, browsers and other software, but it's all contained within the real machine."
The Sandia research, two years in the making, was funded by the Department of Energy's Office of Science, the National Nuclear Security Administration's (NNSA) Advanced Simulation and Computing (ASC) program and by internal Sandia funding.
To complete the project, Sandia utilized its Albuquerque-based 4,480-node Dell high-performance computer cluster, known as Thunderbird. To arrive at the one million Linux kernel figure, Sandia's researchers ran one kernel in each of 250 VMs and coupled those with the 4,480 physical machines on Thunderbird. Dell and IBM both made key technical contributions to the experiments, as did a team at Sandia's Albuquerque site that maintains Thunderbird and prepared it for the project.
The capability to run a high number of operating system instances inside of virtual machines on a high performance computing (HPC) cluster can also be used to model even larger HPC machines with millions to tens of millions of nodes that will be developed in the future, said Minnich. The successful Sandia demonstration, he asserts, means that development of operating systems, configuration and management tools, and even software for scientific computation can begin now before the hardware technology to build such machines is mature.
"Development of this software will take years, and the scientific community cannot afford to wait to begin the process until the hardware is ready," said Minnich. "Urgent problems such as modeling climate change, developing new medicines, and research into more efficient production of energy demand ever-increasing computational resources. Furthermore, virtualization will play an increasingly important role in the deployment of large-scale systems, enabling multiple operating systems on a single platform and application-specific operating systems."
Sandia's researchers plan to take their newfound capability to the next level.
"It has been estimated that we will need 100 million CPUs (central processing units) by 2018 in order to build a computer that will run at the speeds we want," said Minnich. "This approach we've demonstrated is a good way to get us started on finding ways to program a machine with that many CPUs." Continued research, he said, will help computer scientists to come up with ways to manage and control such vast quantities, "so that when we have a computer with 100 million CPUs we can actually use it."
Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin company, for the U.S. Department of Energy's National Nuclear Security Administration. With main facilities in Albuquerque, N.M., and Livermore, Calif., Sandia has major R&D responsibilities in national security, energy and environmental technologies, and economic competitiveness.
Source: Sandia Corp.
In a recent solicitation, the NSF laid out needs for furthering its scientific and engineering infrastructure with new tools to go beyond top performance, Having already delivered systems like Stampede and Blue Waters, they're turning an eye to solving data-intensive challenges. We spoke with the agency's Irene Qualters and Barry Schneider about..
Large-scale, worldwide scientific initiatives rely on some cloud-based system to both coordinate efforts and manage computational efforts at peak times that cannot be contained within the combined in-house HPC resources. Last week at Google I/O, Brookhaven National Lab’s Sergey Panitkin discussed the role of the Google Compute Engine in providing computational support to ATLAS, a detector of high-energy particles at the Large Hadron Collider (LHC).
The Xeon Phi coprocessor might be the new kid on the high performance block, but out of all first-rate kickers of the Intel tires, the Texas Advanced Computing Center (TACC) got the first real jab with its new top ten Stampede system.We talk with the center's Karl Schultz about the challenges of programming for Phi--but more specifically, the optimization...
May 22, 2013 |
At some point in the not-too-distant future, building powerful, miniature computing systems will be considered a hobby for high schoolers, just as robotics or even Lego-building are today. That could be made possible through recent advancements made with the Raspberry Pi computers.
May 16, 2013 |
When it comes to cloud, long distances mean unacceptably high latencies. Researchers from the University of Bonn in Germany examined those latency issues of doing CFD modeling in the cloud by utilizing a common CFD and its utilization in HPC instance types including both CPU and GPU cores of Amazon EC2.
May 15, 2013 |
Supercomputers at the Department of Energy’s National Energy Research Scientific Computing Center (NERSC) have worked on important computational problems such as collapse of the atomic state, the optimization of chemical catalysts, and now modeling popping bubbles.
May 10, 2013 |
Program provides cash awards up to $10,000 for the best open-source end-user applications deployed on 100G network.
05/10/2013 | Cleversafe, Cray, DDN, NetApp, & Panasas | From Wall Street to Hollywood, drug discovery to homeland security, companies and organizations of all sizes and stripes are coming face to face with the challenges – and opportunities – afforded by Big Data. Before anyone can utilize these extraordinary data repositories, however, they must first harness and manage their data stores, and do so utilizing technologies that underscore affordability, security, and scalability.
04/15/2013 | Bull | “50% of HPC users say their largest jobs scale to 120 cores or less.” How about yours? Are your codes ready to take advantage of today’s and tomorrow’s ultra-parallel HPC systems? Download this White Paper by Analysts Intersect360 Research to see what Bull and Intel’s Center for Excellence in Parallel Programming can do for your codes.
In this demonstration of SGI DMF ZeroWatt disk solution, Dr. Eng Lim Goh, SGI CTO, discusses a function of SGI DMF software to reduce costs and power consumption in an exascale (Big Data) storage datacenter.
The Cray CS300-AC cluster supercomputer offers energy efficient, air-cooled design based on modular, industry-standard platforms featuring the latest processor and network technologies and a wide range of datacenter cooling requirements.