Most of the computation was done using idle time on various PCs and on a parallel computing cluster.

By spreading the load of these tasks across many computers, costs that would otherwise be spent on maintaining large computing clusters are avoided.

In 2011, a high-performance computing cluster was created to support advanced computing applications.

It also maintains and operates the scientific computing cluster and the IT infrastructure at HITS.

Instead of using a "tightly-coupled" computing cluster with specialized hardware, arrays of inexpensive RAIN nodes can be assembled.

Cluster file systems, which are file systems that maintain data or indexes in a coherent fashion across a whole computing cluster.

IPython can interactively manage parallel computing clusters using asynchronous status callbacks and/or MPI.

Most high-performance computing clusters use batch processing to maximize cluster usage.

Rocks Cluster Distribution, a Linux distribution intended for high-performance computing clusters.

A job launcher enables users to execute jobs to be executed in the computing cluster.