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Dhiraj Kalamkar
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Harnessing Deep Learning and HPC Kernels via High-Level Loop and Tensor Abstractions on CPU Architectures


Apr 25, 2023
Evangelos Georganas, Dhiraj Kalamkar, Kirill Voronin, Antonio Noack, Hans Pabst, Alexander Breuer, Alexander Heinecke

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DistGNN: Scalable Distributed Training for Large-Scale Graph Neural Networks


Apr 16, 2021
Vasimuddin Md, Sanchit Misra, Guixiang Ma, Ramanarayan Mohanty, Evangelos Georganas, Alexander Heinecke, Dhiraj Kalamkar, Nesreen K. Ahmed, Sasikanth Avancha

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Efficient and Generic 1D Dilated Convolution Layer for Deep Learning


Apr 16, 2021
Narendra Chaudhary, Sanchit Misra, Dhiraj Kalamkar, Alexander Heinecke, Evangelos Georganas, Barukh Ziv, Menachem Adelman, Bharat Kaul

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Tensor Processing Primitives: A Programming Abstraction for Efficiency and Portability in Deep Learning Workloads


Apr 14, 2021
Evangelos Georganas, Dhiraj Kalamkar, Sasikanth Avancha, Menachem Adelman, Cristina Anderson, Alexander Breuer, Narendra Chaudhary, Abhisek Kundu, Vasimuddin Md, Sanchit Misra, Ramanarayan Mohanty, Hans Pabst, Barukh Ziv, Alexander Heinecke

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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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K-TanH: Hardware Efficient Activations For Deep Learning


Oct 21, 2019
Abhisek Kundu, Sudarshan Srinivasan, Eric C. Qin, Dhiraj Kalamkar, Naveen K. Mellempudi, Dipankar Das, Kunal Banerjee, Bharat Kaul, Pradeep Dubey

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* 14 pages, 14 figures 
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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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