With Intel Cloud Edition for Lustre software, users can easily add, remove, or reconfigure AWS resources to match their workloads and budgets for optimal return on investment. In addition, new applications are being designed and deployed exclusively onto the AWS infrastructure for unmatched total cost of ownership (TCO).
Intel Enterprise Edition for Lustre* Software has taken a leap toward greater enterprise capabilities and improved features for HPC with release of version 3.0. This latest version includes new security enhancements, dynamic LNET configuration support, ZFS snapshots, and other features asked for by the HPC community inside and outside the enterprise. Additionally, it adds the Intel Omni-Path Architecture drivers.
A number of industries rely on high-performance computing (HPC) clusters to process massive amounts of data. As these same organizations explore the value of Big Data analytics based on Hadoop, they are realizing the value of converging Hadoop and HPC onto the same cluster rather than scaling out an entirely new Hadoop infrastructure.
This fifth article is an editorial series that explores Lustre solutions in the cloud for an exploding commercial data universe. This week’s looks at Lustre scalability, affordability and manageability.
With the release of Intel® Cloud Edition for Lustre software in collaboration with key cloud infrastructure providers like Amazon Web Services (AWS), commercial customers have an ideal opportunity to employ a production-ready version of Lustre—optimized for business HPDA—in a pay-as-you-go cloud environment.
This week’s lustre 101 article looks at the history of lustre and the typical configuration of this high-performance scalable storage solution for big data applications.
In this video from the 2014 Lustre Administrators and Developers Conference, Brent Gorda from Intel describes how the company is adding enterprise features to the Lustre File System.
In this video from the LAD’14 Lustre Administrators and Developers Conference in Reims, Rekha Singhal from Tata Consultancy Services presents: Performance Comparison of Intel Enterprise Edition Lustre and HDFS for MapReduce Applications.
For a long time, the industry’s biggest technical challenge was squeezing as many compute cycles as possible out of silicon chips so they could get on with solving the really important, and often gigantic problems in science and engineering faster than was ever thought possible. Now, by clustering computers to work together on problems, scientists are free to consider even larger and more complex real-world problems to compute, and data to analyze.
As compute speed advanced towards its theoretical maximum, the HPC community quickly discovered that the speed of storage devices and the underlying the Network File System (NFS) developed decades ago had not kept pace. As CPUs got faster, storage became the main bottleneck in high data-volume environments.