SEATTLE, WA--(Marketwired - Nov 18, 2013) - Global supercomputer leader Cray Inc. (
The Cray Framework for Hadoop package includes documented best practices and performance enhancements designed to optimize Hadoop for the Cray XC30 line of supercomputers. Built with an emphasis on Scientific Big Data usage, the framework provides enhanced support for data sets found in scientific and engineering applications, as well as improved support for multi-purpose environments, where organizations are looking to align their scientific, compute and data-intensive workloads. This enables users to gain the utility of the Java-based MapReduce Hadoop programming model on the Cray XC30 system, complementing the proven, HPC-optimized languages and tools of the Cray Programming Environment.
"We are seeing increased interest from organizations that are ready to leverage Hadoop for analytics in scientific environments, but what those organizations are finding is that Hadoop does not meet all of their needs for scientific use cases," said Bill Blake, senior vice president and CTO of Cray. "They find Hadoop isn't optimized for the large hierarchical file formats and I/O libraries needed by scientific applications that run close to the parallel file systems, or leverage the types of fast interconnects and tightly integrated systems deployed on supercomputers for performance and scalability. And they find it difficult to share infrastructure or manage complex workflows than span both scientific compute and analytics workloads, and being able to integrate math models with data models in a single high-performance environment. With the Cray Framework for Hadoop, we're helping organizations harness the openness and power of Hadoop, while better leveraging the investments and progress they've made in scientific computing."
Based on early customer response, the initial release of the Cray Framework for Hadoop and an optimized Cray Performance Pack for Hadoop will be available as free downloads and include validated and documented best practices for Apache Hadoop configurations. This performance pack includes Lustre-Aware Shuffle to optimize Hadoop performance on the Cray XC30 supercomputer. Further performance enhancements to the performance pack, which will include a native Lustre file system library and a plug-in to further accelerate Hadoop performance using the Aries system interconnect, will be available in the first half of 2014.
The launch of Cray Framework for Hadoop further expands Cray's portfolio of offerings for the rapidly growing Big Data market. Cray's complementary array of Big Data solutions includes fast data and data movement capabilities with Cray® Sonexion® storage systems, a tiered storage and archiving solution with Cray Tiered Adaptive Storage, data discovery using the YarcData uRiKA® appliance, Cray Cluster Supercomputers for Hadoop, and now a growing framework of enhancements and optimizations for running Hadoop workloads on Cray CX30 supercomputers.
About the Cray XC30 supercomputers
Previously code-named "Cascade," the Cray XC30 supercomputers are Cray's most advanced HPC systems and are engineered to meet the performance challenges of today's HPC users. The Cray XC30 and Cray XC30-AC supercomputers feature the unique Aries system interconnect; a Dragonfly network topology that frees applications from locality constraints; innovative cooling systems to lower customers' total cost of ownership; the next-generation of the scalable, high performance Cray Linux Environment supporting a wide range of ISV applications; Cray's HPC optimized programming environment; and the ability to handle a wide variety of processor types.
About Cray Inc.
Global supercomputing leader Cray Inc. (
Safe Harbor Statement
This press release contains forward-looking statements within the meaning of Section 21E of the Securities Exchange Act of 1934 and Section 27A of the Securities Act of 1933, including, but not limited to, statements related to its product development and introduction plans. These statements involve current expectations, forecasts of future events and other statements that are not historical facts. Inaccurate assumptions and known and unknown risks and uncertainties can affect the accuracy of forward-looking statements and cause actual results to differ materially from those anticipated by these forward-looking statements. Factors that could affect actual future events or results include, but are not limited to, the risk that Cray is not able to complete its planned product development efforts or ship the Cray Framework for Hadoop and Cray Performance Pack for Hadoop, and any enhancements to those products, when expected or at all and such other risks as identified in the Company's quarterly report on Form 10-Q for the quarter ended September 30, 2013, and from time to time in other reports filed by Cray with the U.S. Securities and Exchange Commission. You should not rely unduly on these forward-looking statements, which apply only as of the date of this release. Cray undertakes no duty to publicly announce or report revisions to these statements as new information becomes available that may change the Company's expectations.
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