Visit additional Tabor Communication Publications
October 20, 2009
MILPITAS, Calif., Oct. 20 -- Appro, a leading provider of supercomputing solutions, today announces the deployment of Appro Hyper Series Supercomputing Clusters to provide Lawrence Livermore National Laboratory (LLNL) with a new visualization cluster called "Graph," geared specifically to support interactive data analysis and visualization on the extreme-scale Sequoia classified computing systems.
The lab visualization resources provide an essential and critical part of the high performance computing environment enabling computational scientists to interact and explore very large data sets as well as large-scale post-processing and data reduction operations. Development of these capabilities is vital to the National Nuclear Security Administration's (NNSA) program to ensure the safety, security and reliability of the nation's nuclear deterrent without underground testing -- stockpile stewardship. This HPC project required a memory-rich computing with I/O optimized through dedicated file system connections.
Appro deployed to LLNL four Scalable Units (SU)s – 110 TeraFLOP/s Linux clusters. The Graph cluster consists of 564 compute nodes, 2,256 processors / 13,536 cores with 73 TB of memory. Each compute node is based on Six-Core AMD Opteron Processors (code named "Istanbul") at 2.0GHz with 128GB of system memory, 48 Flextronics InfiniBand 20 Gb/s DDR edge switches, and 2 Voltaire DDR Spine switches.
"To meet our current and future scientific computing needs requires a visualization cluster with enough memory to generate visualizations of simulation runs on our largest compute platforms as well as sufficient I/O rates for interactive analysis," said Becky Springmeyer, Visualization group leader in LLNL's Advanced Simulation and Computing Program.
The largest machine to be supported by Graph initially will be Dawn, a 500 teraFLOP/s system delivered earlier this year, followed by Sequoia, a multi-petaFLOP/s system to be delivered in 2011. Sequoia will have 1.6 petabytes of memory, 98,304 compute nodes and 1.6 million cores. These supercomputers are capable of running very large suites of complex simulations and Graph will be capable of supporting complex visualization and analysis tasks on data sets generated on these much larger machines. Visualization specialists are dealing with multi-terabyte data sets with tens of billions of zones, thousands of files per time step, and hundreds of time steps. Post-processing tasks are heavily I/O bound, so specialized visualization servers that optimize I/O rather than CPU speed are better suited for this work. These simulations will be now enabled through Graph.
"The higher end of the HPC market is one of the faster-growing HPC segments and IDC projects that it will continue to see healthy growth over the next 3 to 5 years as more countries and organizations apply very large HPC systems to address leading scientific and engineering problems," said Steve Conway, IDC Research vice president for technical computing. "Appro HPC clusters are designed to give LLNL users significantly more memory and high-speed connections to Lustre than they have on previous LLNL clusters of comparable size. This means that visualization problems can finish faster and more users will be able to post and process their data simultaneously."
"Appro is proud to be able to provide Lawrence Livermore National Laboratory with a powerful visualization cluster that will enable important national security work and push the state-of-the-art in scientific computing on some of the world's most powerful high performance computing systems," said John Lee, VP of Advanced Technology Solutions of Appro.
"Six-Core AMD Opteron processors enable superior performance scalability, helping to allow HPC environments, like the Graph Cluster, to achieve outstanding results," said John Fruehe, director, Business Development, Server and Workstation Division, AMD (NYSE: AMD). "AMD's Direct Connect Architecture and HyperTransport technology with HT Assist help deliver the node memory bandwidth and support for large-scale memory footprints needed for efficient data analysis and complex visualization tasks."
Appro is a leading developer of supercomputing solutions. Appro is uniquely positioned to support high performance computing markets focusing on small to large-scale deployments where lowest total cost of ownership is a primary consideration. Appro accelerates technical applications and business results unlocking the value of IT through outstanding price/performance, balanced architecture, open standards and engineering expertise. Appro headquarters is in Milpitas, Calif., with offices in Korea and Houston, Texas. To learn more, go to http://www.appro.com.
Source: Appro International, Inc.
In quieter times, sounding the bell of funding big science with big systems tends to resonate further than when ears are already burning with sour economic and national security news. For exascale's future, however, the time could be ripe to instill some sense of urgency....
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).
May 23, 2013 |
The study of climate change is one of those scientific problems where it is almost essential to model the entire Earth to attain accurate results and make worthwhile predictions. In an attempt to make climate science more accessible to smaller research facilities, NASA introduced what they call ‘Climate in a Box,’ a system they note acts as a desktop supercomputer.
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.
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.