Today Intel Corporation and BlueData announced a broad strategic technology and business collaboration, as well as an additional equity investment in BlueData from Intel Capital. BlueData is a Silicon Valley startup that makes it easier for companies to install Big Data infrastructure, such as Apache Hadoop and Spark, in their own data centers or in the cloud.
With the launch of Univa Small Jobs add-on for Univa Grid Engine, the company, the company offers “the world’s most efficient processing and lowest latency available for important tasks like real-time trading, transactions, and other critical applications.” To learn more, we caught up with Univa President & CEO Gary Tyreman.
“In this talk, Seagate presents details on its efforts and achievements around improving Hadoop performance on Lustre including a summary on why and how HDFS and Lustre are different and how those differences affect Hadoop performance on Lustre compared to HDFS, Hadoop ecosystem benchmarks and best practices on HDFS and Lustre, Seagate’s open-source efforts to enhance performance of Lustre within “diskless” compute nodes involving core Hadoop source code modification (and the unexpected results), and general takeaways ways on running Hadoop on Lustre more rapidly.”
According to IDC, SGI has shipped approximately 8 percent of of all the Hadoop servers in production today. In fact, did you know that SGI introduced the word “Big Data” to supercomputing in 1996? Jorge Titinger, SGI President and CEO, shares SGI’s history in helping to design, develop, and deploy Hadoop clusters. (NOTE: Straw was substituted for actual hay to avoid any potential allergic reactions.)
From Wall Street to the Great Wall, enterprises and institutions of all sizes are faced with the benefits – and challenges – promised by ‘Big Data’. But before users can take advantage of the near limitless potential locked within their data, they must have affordable, scalable and powerful software tools to manage the data.
“The evolution of Hadoop has very much been a backwards one; it entered HPC as a solution to a problem which, by and large, did not yet exist. As a result, it followed a common, but backwards, pattern by which computer scientists, not domain scientists, get excited by a new toy and invest a lot of effort into creating proof-of-concept codes and use cases. Unfortunately, this sort of development is fundamentally unsustainable because of its nucleation in a vacuum, and in the case of Hadoop, researchers moved on to the next big thing and largely abandoned their model applications as the shine of Hadoop faded.”