DDN King of HPC Storage

DataDirect Networks, Inc. (DDN) continues its leadership of the TOP500.org global supercomputer rankings, today powering nearly half of the world’s 250 largest computers.

As the premier global list that ranks clustered computers by performance, the TOP500 list is a testament to the computer power of clustered computer systems that are being used across HPC markets.

More than two-thirds of the top 100 and one-third of top 500 supercomputers are powered by DDN. Notable new DDN deployments among the top 100 systems include:

No. 2, Oak Ridge National Laboratory;
No. 6, TX Advanced Computing Center at the University of Texas in Austin;
No. 11, Total;
No. 24, the National Energy Scientific Computing Center, and
No. 46, Indiana University.

With major deployments worldwide, DDN also boasts partnerships with leading HPC systems vendors and providers including Bull, Cray, Dell, Fujitsu, HP, IBM and SGI.

With a product portfolio to address the big data and HPC data workflow, DDN continues to show gains among leading commercial HPC practices, including energy exploration, aerospace, automotive, defense, finance, internet.

According to a recent IDC market study, storage is the fastest growing area in HPC sites. As more and more enterprises look to adopt the tools and technologies used in today’s HPC centers, DDN is also seeing an expanding number of commercial use cases for DDN storage.

Delivering scalability and efficiency, DDN products enable HPC clusters to accelerate discovery and minimize the cost of computing.

John Josephakis, SVP of global HPC sales, DDN, said: "For HPC organizations where performance, reliability, scalability and TCO are critical, DDN continues to be the trusted world leader in high-scale cluster computing. We are proud to be the fastest technology that is powering a third of the world’s most powerful computers. This latest TOP500 ranking affirms DDN’s commitment to solving the challenges of high-scalability – and we’re re-investing our successes in the next generation of scale to continue our quest to minimize the cost of computing in the exascale era."