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cs.LG2021
DNN gradient lossless compression: Can GenNorm be the answer?
Zhong-Jing Chen, Eduin E. Hernandez, Yu-Chih Huang +1
In this paper, the problem of optimal gradient lossless compression in Deep Neural Network (DNN) training is considered. Gradient compression is relevant in many distributed DNN tr…
cs.LG2021
Speeding-Up Back-Propagation in DNN: Approximate Outer Product with Memory
Eduin E. Hernandez, Stefano Rini, Tolga M. Duman
In this paper, an algorithm for approximate evaluation of back-propagation in DNN training is considered, which we term Approximate Outer Product Gradient Descent with Memory (Mem-…
cs.DC2021
Straggler Mitigation through Unequal Error Protection for Distributed Approximate Matrix Multiplication
Busra Tegin, Eduin. E. Hernandez, Stefano Rini +1
Large-scale machine learning and data mining methods routinely distribute computations across multiple agents to parallelize processing. The time required for the computations at t…