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PolyDL: Polyhedral Optimizations for Creation of High Performance DL primitives

Jun 02, 2020
Sanket Tavarageri, Alexander Heinecke, Sasikanth Avancha, Gagandeep Goyal, Ramakrishna Upadrasta, Bharat Kaul

* arXiv admin note: substantial text overlap with arXiv:2002.02145 

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Optimizing Deep Learning Recommender Systems' Training On CPU Cluster Architectures

May 10, 2020
Dhiraj Kalamkar, Evangelos Georganas, Sudarshan Srinivasan, Jianping Chen, Mikhail Shiryaev, Alexander Heinecke

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PolyScientist: Automatic Loop Transformations Combined with Microkernels for Optimization of Deep Learning Primitives

Feb 06, 2020
Sanket Tavarageri, Alexander Heinecke, Sasikanth Avancha, Gagandeep Goyal, Ramakrishna Upadrasta, Bharat Kaul

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Training Neural Machine Translation (NMT) Models using Tensor Train Decomposition on TensorFlow (T3F)

Nov 05, 2019
Amelia Drew, Alexander Heinecke

* 10 pages, 2 tables 

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High-Performance Deep Learning via a Single Building Block

Jun 18, 2019
Evangelos Georganas, Kunal Banerjee, Dhiraj Kalamkar, Sasikanth Avancha, Anand Venkat, Michael Anderson, Greg Henry, Hans Pabst, Alexander Heinecke

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A Study of BFLOAT16 for Deep Learning Training

Jun 13, 2019
Dhiraj Kalamkar, Dheevatsa Mudigere, Naveen Mellempudi, Dipankar Das, Kunal Banerjee, Sasikanth Avancha, Dharma Teja Vooturi, Nataraj Jammalamadaka, Jianyu Huang, Hector Yuen, Jiyan Yang, Jongsoo Park, Alexander Heinecke, Evangelos Georganas, Sudarshan Srinivasan, Abhisek Kundu, Misha Smelyanskiy, Bharat Kaul, Pradeep Dubey

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ISA Mapper: A Compute and Hardware Agnostic Deep Learning Compiler

Oct 12, 2018
Matthew Sotoudeh, Anand Venkat, Michael Anderson, Evangelos Georganas, Alexander Heinecke, Jason Knight

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Mixed Precision Training of Convolutional Neural Networks using Integer Operations

Feb 23, 2018
Dipankar Das, Naveen Mellempudi, Dheevatsa Mudigere, Dhiraj Kalamkar, Sasikanth Avancha, Kunal Banerjee, Srinivas Sridharan, Karthik Vaidyanathan, Bharat Kaul, Evangelos Georganas, Alexander Heinecke, Pradeep Dubey, Jesus Corbal, Nikita Shustrov, Roma Dubtsov, Evarist Fomenko, Vadim Pirogov

* Published as a conference paper at ICLR 2018 

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