, ,

Take Care When Updating Your Cluster

Although modern Linux distributions have made it very easy to keep your software packages up-to-date, there are some pitfalls you might encounter when managing your compute cluster.

Cluster software packages are usually not managed from the same software repository as the standard Linux packages, so the updater will unknowingly break compatibility. In particular, upgrading or changing the Linux kernel on your cluster may require manual re-configuration – particularly for systems with large storage, InfiniBand and/or GPU compute processor components. These types of systems usually require that kernel modules or other packages be recompiled against the new kernel.

Please keep in mind that updating the software on your cluster may break existing functionality, so don’t update just for the sake of updating! Plan an update schedule and notify users in case there is downtime from unexpected snags.

You may always contact Microway technical support before you update to find out what problems you should expect from running a software update.

You May Also Like

  • HPC Tech Tips

    Microway Achieves DGX SuperPOD Specialization Partner Status with NVIDIA

    We’re excited to share that Microway has officially achieved the prestigious NVIDIA DGX SuperPOD™ Specialization Partner Status with NVIDIA, to deliver AI factories.  This designation recognizes Microway’s in-house expertise in architecting, building, testing, and delivering advanced AI deployments – and scaling some of the world’s most powerful AI infrastructure.  Read more about the announcement NVIDIA DGX…

  • Hardware

    DGX A100 review: Throughput and Hardware Summary

    When NVIDIA launched the Ampere GPU architecture, they also launched their new flagship system for HPC and deep learning – the DGX 100. This system offers exceptional performance, but also new capabilities. We’ve seen immediate interest and have already shipped to some of the first adopters. Given our early access, we wanted to share a…

  • HPC Tech Tips

    Deploying GPUs for Classroom and Remote Learning

    As one of NVIDIA’s Elite partners, we see a lot of GPU deployments in higher education. GPUs have been proving themselves in HPC for over a decade, and they are the de-facto standard for deep learning research. They’re also becoming essential for other types of machine learning and data science. But GPUs are not always…