SAN JOSE, Calif., Aug. 01, 2018 /PRNewswire-PRWeb/ — Today, Bright Computing, a global leader in cluster and cloud infrastructure automation software, announced that Bright partner, Data In Science Technologies, has successfully implemented Bright Cluster Manager 8.1 for Fayetteville State University.

Fayetteville State University first became a Bright Computing customer in August 2017, when it chose to deploy Bright Cluster Manager for use in ground-breaking Artificial Intelligence (AI) research. Bright technology was installed to support Fayetteville’s specific advances in deep architectures for artificial neural networks, to build an automated computer system that could analyze text and video data.

In June 2018, Fayetteville engaged with Bright Computing’s Services Partner, Data In Science, to implement Bright Cluster Manager Version 8.1. The latest version of Bright technology includes many new features and functionality to make it even easier to create and manage Linux clusters:

•     New workload management accounting and reporting capabilities
•     Expanded deep learning capability in Bright Cluster Manager for Data Science
•     Cloud bursting to OpenStack allows clusters to extend into a private OpenStack cloud
•     Lightweight cluster management daemon exposes monitoring and health checking APIs
•     Improved Ceph Support for BlueStore, the new storage backend for Ceph
•     Advanced Kubernetes integration

Data In Science Technologies (DST) is a Bright Computing Reseller and Services Partner. DST provides expertise, problem resolution and architecture design for some of the largest private and public HPC clusters in the world. Its service comprises state of the art tools, proven methodologies, and senior level engineers to make sure Bright Cluster Manager and the HPC cluster operates at peak performance, and is strategically deployed.

During the Bright Cluster Manager upgrade, DST carried out the following processes:

•     Inspect system state, queues and health
•     Backup OS, applications and settings
•     Image update – Bright Cluster Manager code
•     Scheduler – Update and test
•     Bright Node Head Manager OS Upgrade – RHEL 7 to REHL 7.x and Bright 7 to Bright 8.x
•     Distribution of Alternative Linux, Ubuntu, SLES
•     Post-install knowledge transfer to show how Bright Cluster Manager is configured
•     DST extras included MatLab and FastX Implementation for customer defined needs

Dr. Sambit Bhattacharya, Associate Professor of Computer Science at Fayetteville State University, commented, “Bright Cluster Manager is the obvious choice for our clustered infrastructure needs. So, upgrading to the latest version made perfect sense. We are delighted with the close relationship we have built with Data In Science in order to carry out the upgrade quickly, and cause minimal impact to daily business.”

Don Schrenk, Senior Partner at DST, added, “Our partnership with Bright Computing is a winner. We utilize Bright to manage our customer environments today and understand the value that Bright technology brings and are therefore in a strong position to install Bright solutions in customer environments, seamlessly and cost-effectively. The team at Fayetteville are highly skilled and place high technical demands on their HPC infrastructure, so we are delighted to deliver such a robust solution to them.”

Clemens Engler, Director Alliances, concluded, “The latest version of Bright Cluster Manager offers a wealth of new features that organizations like Fayetteville State University benefit from. I am delighted to see our relationship with Services Partner DST flourish so that together we can deliver industry-leading solutions to satisfy evolving customer requirements.”

SOURCE BRIGHT COMPUTING