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Sasikanth Avancha

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DistGNN-MB: Distributed Large-Scale Graph Neural Network Training on x86 via Minibatch Sampling

Nov 11, 2022
Md Vasimuddin, Ramanarayan Mohanty, Sanchit Misra, Sasikanth Avancha

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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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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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Deep Graph Library Optimizations for Intel(R) x86 Architecture

Jul 13, 2020
Sasikanth Avancha, Vasimuddin Md, Sanchit Misra, Ramanarayan Mohanty

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Hardware Acceleration of Sparse and Irregular Tensor Computations of ML Models: A Survey and Insights

Jul 02, 2020
Shail Dave, Riyadh Baghdadi, Tony Nowatzki, Sasikanth Avancha, Aviral Shrivastava, Baoxin Li

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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

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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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SEERL: Sample Efficient Ensemble Reinforcement Learning

Jan 15, 2020
Rohan Saphal, Balaraman Ravindran, Dheevatsa Mudigere, Sasikanth Avancha, Bharat Kaul

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