44 citations · 59 across the 3 of their papers we have counts for
3 papers
cs.CV2017★ 44 cited
Low-memory GEMM-based convolution algorithms for deep neural networks
Andrew Anderson, Aravind Vasudevan, Cormac Keane +1
Deep neural networks (DNNs) require very large amounts of computation both for training and for inference when deployed in the field. A common approach to implementing DNNs is to r…
cs.CV2017★ 13 cited
Parallel Multi Channel Convolution using General Matrix Multiplication
Aravind Vasudevan, Andrew Anderson, David Gregg
Convolutional neural networks (CNNs) have emerged as one of the most successful machine learning technologies for image and video processing. The most computationally intensive par…
cs.DC2017★ 2 cited
Mutual Inclusivity of the Critical Path and its Partial Schedule on Heterogeneous Systems
Aravind Vasudevan, David Gregg
The critical path of a group of tasks is an important measure that is commonly used to guide task allocation and scheduling on parallel computers. The critical path is the longest…