the Bright blog

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Hybrid Computing in the New Era of HPC

By Bright Staff | January 06, 2021

Across industries such as healthcare, manufacturing, agriculture, financial, etc., edge computing has become more complex and nuanced as the digital age has progressed.

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University of Vigo Selects Bright Cluster Manager

By Terry Rush | December 15, 2020

We are really pleased that the University of Vigo in Spain has chosen Bright Cluster Manager to build and manage its HPC Linux cluster. 

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New Supercomputer “Ookami” Installed at Stony Brook, Underpinned By Bright

By Lee Carter | November 13, 2020

I was thrilled to read in the news today, that the Ookami computer at Stony Brook University has been launched and is now available to researchers nationwide as a testbed for exciting new high-performance computing technology. 

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Dell EMC Ready Solutions for HPC Accelerate Customers' Time to Deliver New Products and Services

By Grant Gustafson | November 09, 2020

Here at Bright, we are honored to have such great partnership with companies like Dell Technologies. So, we were delighted to see their announcement today regarding two new Ready Solutions for HPC Genomics and Digital Manufacturing.

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Improving Capacity Planning for Important Environment Research with DHI Group

By Terry Rush | November 06, 2020

In case you missed the press release that we issued on Wednesday this week, the DHI Group -  a long-standing customer of Bright Computing - has once again chosen Bright technology to underpin its new compute environment. And, I’m pleased to say that the DHI Group will be putting us to good use. They will leverage the full-featured Bright Cluster Manager software platform to support pioneering environmental research projects; a matter close to all of our hearts.

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How to export data from Bright: Taking a look at Prometheus exporter

By Martijn de Vries | April 24, 2020

Even though Bright Cluster Manager provides a fantastic monitoring environment for high performance computing, AI, data science, big data, OpenStack, machine and deep learning environments, it’s important to recognize that a Bright cluster is not an island in an organization's IT infrastructure. Many organizations will have infrastructure-wide monitoring and reporting environments in place, in addition to Bright’s capabilities. We also have to accept that there may be companies that wish to use monitoring tools other than Bright View to see monitoring data.

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How to create Bright clusters in Microsoft Azure and AWS using a cluster on demand Docker container

By Martijn de Vries | April 14, 2020

For the majority of our customers, the usual way of installing a Bright cluster is by downloading the Bright ISO, going through a head node installation, and then PXE booting your compute nodes to allow them to join the cluster.

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High Performance Clusters in the Cloud?

By Bill Harries | April 07, 2020

Now, why would I want to do that? Cloud resources can be expensive; I have to depend on a third party for some of my most important applications; performance may suffer; my data ends up outside my organization…all valid concerns. Which likely explains why most HPC continues to be hosted in-house. But another question is, is it even an option to effectively leverage the cloud for clustered computing? How do I extend my on-premise cluster to cloud servers and still manage them as a single cluster?

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Pushing Monitoring Data into your Bright Cluster

By Martijn de Vries | March 31, 2020

Whether you are a Bright customer, a Bright reseller, or in the process of evaluating Bright, you will be aware that Bright Cluster Manager is great at monitoring your cluster. From the moment that you set up your cluster for the first time, Bright’s monitoring capabilities set to work, providing comprehensive metrics and alerts.

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The WAR against inefficient HPC cluster resource utilization

By Robert Stober | March 27, 2020

To extract the most value from your HPC cluster, you need to ensure that system resources are being properly utilized.  HPC system users are notorious for over-requesting resources for their jobs, resulting in idle or underutilized resources that could otherwise be doing work for other jobs.  While one reason for this can be users hoarding resources to ensure they have what they need, another common reason why users over request resources is that they simply don’t know what resources their jobs will need to complete the job in a specified time.  For administrators to ensure that their precious and expensive cluster resources aren’t being squandered, they need to get actionable details regarding how the resources are being used.  More specifically, they need to know things like which jobs are using which resources, which jobs aren’t using resources that they’ve provisioned and which users are repeatedly hoarding resources unnecessarily, as well as other things.

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