Caffe (Convolutional Architecture for Fast Feature Embedding) is a deep learning framework, originally developed at University of California, Berkeley.

[5] Yangqing Jia created the Caffe project during his PhD at UC Berkeley, while working the lab of Trevor Darrell.

[8] Caffe supports GPU- and CPU-based acceleration computational kernel libraries such as Nvidia cuDNN and Intel MKL.

[9][10] Caffe is being used in academic research projects, startup prototypes, and even large-scale industrial applications in vision, speech, and multimedia.

has also integrated Caffe with Apache Spark to create CaffeOnSpark, a distributed deep learning framework.