CPU and GPU - What's the difference?

CPU nodes perform sequential processing and are best suited for general tasks. This setting will allow users to perform various tasks, such as complex calculations and running applications. CPU will utilise several cores with lower latency (delays in processing) making it ideal for executing single-threaded tasks at a faster rate. Using the Change Settings button to reveal the Setting options allows users to configure their desktops with more cores.

CPU node is most useful for:

• Data Preparation

• Feature Extraction

• Small Scale Models

• Complex Calculations with smaller data sets

GPU nodes deliver more performance and make use of parallel processing. GPU utilises a high number of cores however it has a higher latency (delays in processing). It is ideal for parallel processing making use of multi-threaded tasks to perform more efficiently. This makes the GPU node beneficial for machine learning or scientific computations because it can parallelise and run repetitive tasks quickly.

GPU Node is most useful for:

• Machine Learning with Python packages

• Faster results for data analysis with intensive data sets.

• Processing large-scale images, including drone images

• Run analysis on acoustic data

• Training models

• Image processing