Following up to our recent blog about the availability of Univa Grid Engine for ARM, Jeff Underhill of ARM has posted a blog about news in the ecosystem which demonstrate that the ARM CPU architecture becomes an ever more viable option for a broad set of applications including high performance, high throughput and high capacity computing. In his blog Jeff also covers Univa Grid Engine and the benefits it brings to ARM environments. Read here for more information.

From the Blog of Daniel Gruber - Grid Engine developer

A compute cluster or grid often varies in the hardware installed. Some compute nodes offers processors with strong compute capabilities while others are older and slower. This becomes an issue when parallel compute jobs are submitted to a job/cluster scheduler. When the jobs runs on slower hardware it should use more compute cores than on faster cores. But during submission time the parameters (like the amount of cores used for core binding) are often fixed.

Join Archimedes Inc and Univa as they explore shared infrastructures including Hadoop in production.

Featuring the cutting-edge case study from Archimedes Inc., developer of the Archimedes Model, whose mission is to revolutionize the quality and efficiency of healthcare worldwide through mathematics. As Archimedes' business scaled to support more users, complex diseases and health outcomes, the pressure was on to ensure the IT infrastructure could keep up to the demands of the business for a reasonable cost. Please join our webinar on Thu, Mar 21 2013 from 12:00-01:00 PM Easter Time to learn

Clusters are very often heterogenous in the amount of cores each server employs and in the relative speed of these cores. Univa Grid Engine provides a means to enable adaptive scheduling taking respect to this heterongeity since version 8.1.3. In this latest entry of our Engineer's Talk channel veteran Grid Engine developer Daniel Gruber explains the details. Read more ...

Archimedes, a healthcare modeling organization, develops the Archimedes Model, a clinically realistic, mathematical model of human physiology, diseases, interventions and healthcare systems. When the company sought to improve the time to results for its clients it developed new software called Aggregator using the open-source Big Data solution, Hadoop®, a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models.

Archimedes then faced the challenge of deploying and managing Hadoop and needed to find a solution that