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Artificial Intelligence & Machine Learning vocabulary · Deployment and MLOps

GPU

Meaning in artificial intelligence & machine learning, with examples

/ˌdʒiː piː ˈjuː/abbreviationCore term

In artificial intelligence & machine learning, GPU means: Short for graphics processing unit: a chip that does thousands of simple calculations in parallel, which makes it the main hardware for training and running neural networks.

In Turkish: grafik işlem birimi, ekran kartı

How it is used

Engineers talk about GPU memory, GPU hours, GPU clusters and GPU utilization, and about renting GPUs in the cloud. Model sizes are often discussed in terms of how many GPUs they need. Related chips include TPUs and other AI accelerators.

Example sentences

  1. The 70B model needs at least two of our GPUs just to load.

  2. GPU utilization is only 30%, so the data loader is probably the bottleneck.

Common collocations

  • GPU memory
  • GPU hours
  • GPU cluster
  • rent GPUs
  • GPU utilization
  • inferenceThe stage in which a trained model is used to produce outputs for new inputs, for example answering a user's question or classifying a new photo.
  • batch sizeThe number of training examples a model processes together before it updates its parameters once.
  • quantizationStoring a model's weights, and sometimes its activations, with fewer bits, for example 8-bit or 4-bit numbers instead of 16-bit, to make it smaller and faster.
  • deep learningThe part of machine learning that uses neural networks with many layers. It powers modern speech recognition, image recognition and large language models.

This word in other fields

The same English word can have a different meaning in another field:

More terms: Deployment and MLOps

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