This distributed computing system, comprising some 12,000 cores, is used by SU faculty and researchers, particularly in the physical sciences and engineering, who need reliable, high throughput computing (HTC). The computers in the grid are optimized to perform a large number of smaller parallel jobs (typically less than 24 hours), providing high processing capacity over long periods of time.
OrangeGrid is supported by ITS, Syracuse’s central IT group, and offered to researchers without cost. The grid is unique in that approximately 20% of the nodes on the network are upgraded annually as part of regular campus desktop replacement cycles, providing a notable increase in processing and memory capacity each year.
These components are distributed to desktop clients via Microsoft’s Active Directory. HTCondor, developed with support from the National Science Foundation, manages the grid’s workload. The computer’s task scheduler detects when its host computer is idle, starts up CVMC, and connects to HTCondor to receive work. When user activity is detected on the computer, research operations are immediately stopped. The use of virtualization acts as a barrier which separates the researcher and their content from the user’s information on the same computer.
Header Image Credit:
Barrett Lyon / The Opte Project
Visualization of the routing paths of the Internet.
Condor works by match-making jobs in the queue to available machines in the pool So far we have seen the two key elements of the pool: the job queue, which is displayed by condor_q and the pool status which is displayed by condor_status. We will see how this works...
The Campus OrangeGrid Pool is a collection of compute resources available free of charge to SU researchers. The compute power for the Syracuse University Campus OrangeGrid Pool comes from unused CPU cycles from desktop machines across the campus. When a desktop...
OrangeGrid Computing Almost any computational problem can be solved on a single computer. However, when you encounter problems that are too large (or take too long) to be solved on a single machine you will need to use a computing cluster to complete your...