Univa Grid Engine, the enterprise-grade workload manager with first-class support for container workloads, meets Azure CycleCloud in the simplest way to manage high-performance computing (HPC) workloads. This collaboration realizes end-to-end enterprise support for HPC workloads running on Azure – including a free, pre-configured demo experience to explore and learn more about the capabilities of this combined offering. You will find a Univa Grid Engine demo cluster with rich autoscaling capabilities, ready to dive into in CycleCloud 8.
Grid scalability has been a consistent focus for both Univa and Azure; with this offering, customers will benefit from scheduling efficiencies and elasticity – graduate to a fully-licensed version of Univa Grid Engine to unlock cloud computation and increase its speed on a staggering scale. Univa Grid Engine provides extraordinary scale, and precise resource allocation at scale. Close collaboration brings resource-awareness throughout the stack – if you specify 4 NVIDIA Tesla V100 GPUs in the job requirements, then 4 GPUs will be added to the grid, or 400 or 4000.
Introduced as part of CycleCloud 8 is multi-dimensional autoscaling. Complex job requirements such as memory, CPUs, GPUs will all be evaluated, and the grid will scale to meet all requirements for all jobs – in a minimal fashion. Univa Grid Engine jobs with resource requirements will translate to real grid resources through CycleCloud. Also available are tunable scale-down parameters to reduce size as resources become idle. You can toggle between fill-up and round robin resource autoscaling logic to be more cost-conservative or performance-driven. This resource allocation is distinct from job scheduling – where all the rich scheduling resources provided by Univa Grid Engine are available. The combined solution is a resource-aware highly elastic HPC compute environment.
This solution brings first-class support for Azure Infiniband networking capabilities. Dedicate specific Univa Grid Engine hostgroups for specific Infiniband fabrics so that tightly coupled jobs run on the most performant network – all automatically when you use the MPI parallel environment (or configure your own Univa Grid Engine PE to use IB).
We are proud to offer the leading distributed resource management system that optimizes workloads to Azure CycleCloud 8 users. Contact us to upgrade from the pre-configured demo version cluster to an unlocked version of Grid Engine to reach enterprise scale and support.