High-Performance Computing has undoubtedly changed in the last few years and administrators are frequently tasked with supporting unusual request. Gone are the days of all HPC cluster users being script savvy Computer Scientists who speak BASH as fluently as they do English.
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If you’re working in deep learning using NVIDIA GPUs, you may have heard about the NVIDIA GPU Cloud or NGC for short. NGC provides pre-integrated GPU-accelerated containers that you can use power your own AI projects.
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Our 9-part blog smackdown between containerization and virtualization continues today with a look at two topics: start time and setup orchestration.
For new readers, we are deep into our “wrestling match” – a friendly contest between Taras Shapovalov, (team container) Piotr Wachowicz (team VM). The battle royal includes:
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Continuing our 8-part blog smackdown between containerization and virtualization, today we are going to dive deeper into overhead. We’ll discuss how much virtual machine (VM) overhead can be reduced with the right know-how and tools and how that matches up with containerization overhead.
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Containers are the hot topic at many if not most of the IT conferences I have attended recently. Containerization has definitely invaded the territory of virtualization, with many saying that containerization wins in a beat down. Does industry even need VMs anymore?
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In our latest vodcast, we review three significant improvements in Bright Cluster Manager for HPC in 7.2 – job-based metrics, support for containers with Docker and Kubernetes, and enhanced Puppet integration.
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