Learn how to effectively schedule and manage your system workload using Slurm; the free, open source and highly scalable cluster management and job scheduling system for Linux clusters. Slurm is in use today on roughly half of the largest systems in the world servicing a broad spectrum of applications. Slurm developers have been working closely with NVIDIA to provide capabilities specifically focused on the needs of GPU management. This includes a multitude of new options to specify GPU requirements for a job in various ways (GPU count per job, node, socket and/or task), additional resource requirements for allocated GPUs (CPUs and/or memory per GPU), how spawned tasks should be bound to allocated GPUs, and control over GPU frequency and voltage. An introduction to Slurm's design and capabilities will be presented with a focus on managing workloads for GPUs.
A shared physical graphics processor unit (GPU) exposed to virtual guests as a virtual GPU drastically changes the dynamics of what is possible from both a technical and monetary standpoint in high tech virtual workstations. You are able to run lots of GPU based workloads in multiple VMs on one host utilizing NVIDIA Tesla cards. Attendees will learn about vGPU technology, Virtual Function IO (VFIO) and associated roadmaps.
We'll discuss the benefits of virtual GPU (vGPU) and Linux for technical workstation use cases and how and when the cooperation of NVIDIA and Red Hat is getting this to the market. A shared physical GPU, exposed to virtual guests as a vGPU, drastically changes the dynamics of what is possible from both a technical and monetary standpoint in high-tech virtual workstations. We'll provide a brief overview of 3D acceleration and compute provided by NVIDIA and Red Hat technologies and what it means for high-tech virtual workstations. Learn about density, vGPUs, VFIO, endpoints, roadmaps, and where to find out more information.