Project Info

Accelerating Inference of Recurrent Neural Networks on GPUs

Bo Wu | bwu@mines.edu

Recurrent neural networks is widely used in domains, such as document understanding, machine translation, and sequence prediction. Although GPUs have shown their tremendous power in model training, inference of recurrent neural networks cannot efficiently utilize GPUs due to the limited parallelism. This project aims at designing a scheduling framework to accelerate inference on GPUs by more than 10 times.

More Information

http://www.wildml.com/2015/09/recurrent-neural-networks-tutorial-part-1-introduction-to-rnns/

https://www.nvidia.com/content/tegra/embedded-systems/pdf/jetson_tx1_whitepaper.pdf

Grand Engineering Challenge: Not applicable