Workload Scheduling and Management
Posted in Univa
Univa Grid Engine helps organizations improve ROI and deliver better results faster by optimizing throughput and performance of applications, containers and services and maximizing shared compute resources across on-premise, hybrid and cloud infrastructures.
Univa Grid Engine Features
Grid Engine software manages workload placement automatically, maximizes shared resources, supports extreme scale, provides enterprise-grade dependability and accelerates deployment of any container, application or service in any technology environment, on-premise or in the cloud.
Run containers, such as Docker or Singularity, in a Univa Grid Engine cluster at scale and blend containers with other workloads supporting heterogeneous applications and technology environments.
Get the most out of GPU-powered servers by optimally mapping Machine Learning, HPC or other GPU-based workloads onto the complex topology of GPU servers in clusters or clouds.
Univa Grid Engine Add-On
Sharing and use of limited, often costly, application license features across users, groups, departments, or projects.
Univa Grid Engine is the path to scaled up data centers and will support any existing environment.
Broadest Operating System Support
Container and Microservices Support
Extensive Hardware Support
Wide Application & Framework Support