CNN Inference Task

A CNN Inference Task is a neural network inference task for a CNN model.

• See: CNN Training.

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References

2017

• (Parashar et al., 2017) ⇒ Angshuman Parashar, Minsoo Rhu, Anurag Mukkara, Antonio Puglielli, Rangharajan Venkatesan, Brucek Khailany, Joel Emer, Stephen W Keckler, and William J Dally. (2017). “SCNN: An Accelerator for Compressed-sparse Convolutional Neural Networks.” In: ACM SIGARCH Computer Architecture News, 45(2).
  • QUOTE: ... Convolutional neural networks (CNNs) have become the most popular algorithmic approach for deep learning for many of these domains. Employing CNNs can be decomposed into two tasks: (1) training — in which the parameters of a neural network are learned by observing massive numbers of training examples, and (2) inference — in which a trained neural network is deployed in the field and classifies the observed data. Today, training is often done on GPUs [24] or farms of GPUs, while inference depends on the application and can employ CPUs, GPUs, FPGA, or specially-built ASICs. …

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