1. Albericio J, Judd P, Hetherington T, et al., 2016. Cnvlutin: ineffectual-neuron-free deep neural network computing. Proc 43rd Int Symp on Computer Architecture, p.1–13. https://doi.org/10.1145/3007787.3001138
2. Alwani M, Chen H, Ferdman M, et al., 2016. Fused-layer CNN accelerators. 49th Annual IEEE/ACM Int Symp on MICRO, p.1–12. https://doi.org/10.1109/MICRO.2016.7783725
3. Anwar S, Hwang K, Sung W, 2017. Structured pruning of deep convolutional neural networks. ACM J Emerg Technol Comput Syst, 13(3), Article 32. https://doi.org/10.1145/3005348
4. Cai Z, He X, Sun J, et al., 2017. Deep learning with low precision by half-wave Gaussian quantization. IEEE Computer Society Conf on Computer Vision and Pattern Recognition, p.5918–5926.
5. Chen L, Li J, Chen Y, et al., 2017. Accelerator-friendly neural-network training: learning variations and defects in RRAM crossbar. Proc Conf on Design, Automation and Test in Europe Conf and Exhibition, p.19–24.