/tag/dcos

  • Computing Environments at UVA

    Rivanna The primary vehicle for high-performance computing since 2014 has been the Rivanna cluster. Rivanna is a heterogenous system consisting of approximately 186 x 20-core nodes with 128GB of RAM each, 25 x 28-core nodes with 256 GB of RAM, and 152 x 40-core nodes with 384GB each. Five “big memory” nodes offer 1TB of RAM with 16 cores each. All nodes are supported by a high-performance FDR Infiniband network using Mellanox hardware and some have EDR Infiniband. A number of nodes supporting specialty hardware are included; there are 8 nodes with NVIDIA K80 GPGPUs, 4 nodes with NVIDIA V100 GPGPUs, 1 node with NVIDIA V100, and 2 nodes with NVIDIA RTX2080TI boards.
  • DCOS Microservices

    Microservice architecture is an approach to designing and running applications. Such applications are typically run within containers, made popular in the last few years by Docker. Containers are portable, efficient, and disposable, and contain code and any dependencies in a single package. Containerized microservices typically run a single process, rather than an entire stack within the same computing environment. This allows portions of your application to be easily replaced or scaled as needed. Microservices at UVA Research Computing runs microservices in an orchestration environment named DCOS (Distributed Cloud Operating System), based on Apache Mesos and Apache Marathon. DCOS makes the deployment and management of many containers easy and scalable.
  • DCOS Container Request

    – Name * E-mail * User ID * Classification * - Select -FacultyStaffPostdoctoral AssociateOther Affiliation * - Select - College of Arts & Sciences School of Data Science School of Engineering and Applied Sciences School of Medicine Darden School of Business UVA Health System Other Project Summary Please describe your project and the container images you want to run in DCOS. Tier of Service *     6 - 15 containers ($10/month total)   15 containers ($48/month total) Billing Tiers are selected and paid for by the PI.