We designed our computing clusters (a large, powerful pool of computers) around open standards for reliability, scalability, extensibility, and interoperability. We use hardware from major vendors and a standard, enterprise-grade Linux distribution customized to address the specific needs of our users. Our infrastructure is designed to provide the greatest possible range of options to you, rather than obliging you to restrict yourself to a narrow range of tools and methodologies. We provide a stable platform on which a wide range of technologies can be deployed.
Our computing clusters consist of two main pools of resources:
Batch processing is intended for long-running processes that are CPU intensive and able to run in parallel. Batch servers enables users to perform multiple commands and functions without waiting for results from one set of instructions before beginning another, and to execute these processes without being present.
Interactive servers are intended for large processes that are memory intensive. Our interactive cluster allows users to view and engage with their jobs in real time.
Both batch and interactive servers at HMDC run on a high throughput cluster, based on HTCondor, on which users can perform extensive, time-consuming calculations without the technical limitations imposed by a typical workstation. Our computing clusters use parallel processing to enable faster execution of computation-intensive tasks. Many computing tasks can benefit from implementation in a parallel processing form. The cluster is extremely useful for the following applications:
Jobs that run for a long time: You can submit a batch processing job that executes for days or weeks and does not tie up your RCE session during that time.
Jobs that are too big to run on your desktop: You can submit jobs that requires more infrastructure than your workstation provides. For example, you could use a dataset that is larger in size than the memory on your workstation.
Groups of dozens or hundreds of jobs that are similar: You can submit batch processing that entails multiple uses of the same program with different parameters or input data. Examples of these types of submission are simulations, sensitivity analysis, or parameterization studies.
Access to our computing clusters is available to all RCE users.