@conference {8695654,
	title = {Characterizing Sources of Ineffectual Computations in Deep Learning Networks},
	booktitle = {2019 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)},
	year = {2019},
	note = {n/a},
	month = {March},
	pages = {165-176},
	abstract = {n/a},
	keywords = {Computational modeling, convolutional neural nets, Convolutional neural networks, deep learning acceleration, deep learning networks, Hardware, hardware accelerators, Image classification, image classification models, image classification networks, image resolution, Image segmentation, imaging, ineffectual computations, Ineffectual Work, inference, inference mechanisms, learning (artificial intelligence), Long-Short-Term-Memory models, memory bandwidth, Natural Language Processing, neural nets, neural networks, performance gains, Precision, Quantization (signal), sparsity},
	issn = {null},
	doi = {10.1109/ISPASS.2019.00030},
	author = {M. {Nikoli{\'c}} and Mahmoud, M and A. {Moshovos} and Y. {Zhao} and R. {Mullins}}
}
