September 06, 2012
SAS solution for business analytics, workload balancing and predictive modeling records fastest runtimes ever when paired with industry-leading big data solutions from DDN in SAS laboratory testing
CHATSWORTH, Calif., Sept. 6 — DataDirect Networks (DDN), the leader in massively scalable storage, today announced that the award-winning DDN SFA 10K-E platform with the DDN GRIDScaler parallel file system produced the fastest runtimes recorded to date by SAS labs for a SAS Grid execution of a highly parallel model calibration workload. SAS engineers also concluded in recent testing that DDN GRIDScaler offered the most consistent and predictable performance of any shared file system tested to date with SAS Grid Computing, supporting applications such as SAS Drug Development, SAS Warranty Analysis and SAS Enterprise Miner for fraud detection, risk management and enterprise business optimization.
The full benchmark results have been published in a SAS white paper available at http://support.sas.com/rnd/scalability/grid/SASGridDDN.pdf.
"DDN and SAS share a common mission: to help organizations extract the greatest possible value from their data," said Jean-Luc Chatelain, Executive Vice President, Strategy and Technology at DDN. "Paired together, DDN and SAS technologies unleash the incredible potential of the Big Data era and accelerate the speed of business."
The DDN SFA 10K-E is a unified virtual server and storage appliance featuring DDN's groundbreaking In-Storage Processing technology. This virtualized environment eliminates externalized data processing systems and allows data-intensive applications to exist within the storage engine – expediting data access, minimizing latency and significantly lowering the cost and complexity of data-intensive computing.
"The DDN SFA 10K-E platform with the DDN GRIDScaler parallel file system is an excellent choice for SAS Grid deployments," said Cheryl Doninger, Senior Director, Research and Development, SAS. "IO intensive SAS Grid workloads have demonstrated excellent performance characteristics utilizing this storage appliance. The choice of shared file system and storage is a critical component of high-performance SAS Grid deployments."
SAS Grid Computing enables organizations to create a managed, shared environment to process large volumes of data and analytic programs more efficiently, making it easier and cost-effective to scale compute-intensive applications for greater complexity and more users.
For more information on the DDN SFA platform, click here: http://www.ddn.com/en/products/SFA12K.
For more information on DDN GRIDScaler, click here: http://www.ddn.com/en/products/gridscaler-file-storage-system.
About DataDirect Networks
DataDirect Networks (DDN) is the world leader in massively scalable storage. We are the leading provider of data storage and processing solutions and professional services that enable content-rich and high growth IT environments to achieve the highest levels of systems scalability, efficiency and simplicity. DDN enables enterprises to extract value and deliver results from their information. Our customers include the world's leading online content and social networking providers, high performance cloud and grid computing, life sciences, media production organizations and security & intelligence organizations. Deployed in thousands of mission critical environments worldwide, DDN's solutions have been designed, engineered and proven in the world's most scalable data centers to ensure competitive business advantage for today's information powered enterprise. For more information, go to www.ddn.com or call +1-800-TERABYTE (837-2298).
Source: DataDirect Networks
The ever-growing complexity of scientific and engineering problems continues to pose new computational challenges. Thus, we present a novel federation model that enables end-users with the ability to aggregate heterogeneous resource scale problems. The feasibility of this federation model has been proven, in the context of the UberCloud HPC Experiment, by gathering the most comprehensive information to date on the effects of pillars on microfluid channel flow.
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).
Frank Ding, engineering analysis & technical computing manager at Simpson Strong-Tie, discussed the advantages of utilizing the cloud for occasional scientific computing, identified the obstacles to doing so, and proposed workarounds to some of those obstacles.
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 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.
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.
04/02/2012 | AMD | Developers today are just beginning to explore the potential of heterogeneous computing, but the potential for this new paradigm is huge. This brief article reviews how the technology might impact a range of application development areas, including client experiences and cloud-based data management. As platforms like OpenCL continue to evolve, the benefits of heterogeneous computing will become even more accessible. Use this quick article to jump-start your own thinking on heterogeneous computing.