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K-TanH: Hardware Efficient Activations For Deep Learning., , , , , , , , and . CoRR, (2019)On Scale-out Deep Learning Training for Cloud and HPC., , , , , , , , , and 1 other author(s). CoRR, (2018)A Study of BFLOAT16 for Deep Learning Training., , , , , , , , , and 9 other author(s). CoRR, (2019)Ternary Residual Networks., , , , , , and . CoRR, (2017)ScaleDeep: A Scalable Compute Architecture for Learning and Evaluating Deep Networks., , , , , , , , , and 1 other author(s). ISCA, page 13-26. ACM, (2017)X-MANN: A Crossbar based Architecture for Memory Augmented Neural Networks., , , , , and . DAC, page 130. ACM, (2019)Automatic Model Parallelism for Deep Neural Networks with Compiler and Hardware Support., , and . CoRR, (2019)Exploring Shared-Memory Optimizations for an Unstructured Mesh CFD Application on Modern Parallel Systems., , , , , , , , , and . IPDPS, page 723-732. IEEE Computer Society, (2015)High Performance Non-uniform FFT on Modern X86-based Multi-core Systems., , , , , , , , , and . IPDPS, page 449-460. IEEE Computer Society, (2012)Mixed Precision Training of Convolutional Neural Networks using Integer Operations., , , , , , , , , and 7 other author(s). ICLR (Poster), OpenReview.net, (2018)