124 citations · 311 across the 19 of their papers we have counts for
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PolyDL: Polyhedral Optimizations for Creation of High Performance DL primitives
Sanket Tavarageri, Alexander Heinecke, Sasikanth Avancha +3
Deep Neural Networks (DNNs) have revolutionized many aspects of our lives. The use of DNNs is becoming ubiquitous including in softwares for image recognition, speech recognition,…
Optimizing Deep Learning Recommender Systems' Training On CPU Cluster Architectures
Dhiraj Kalamkar, Evangelos Georganas, Sudarshan Srinivasan +3
During the last two years, the goal of many researchers has been to squeeze the last bit of performance out of HPC system for AI tasks. Often this discussion is held in the context…
PolyScientist: Automatic Loop Transformations Combined with Microkernels for Optimization of Deep Learning Primitives
Sanket Tavarageri, Alexander Heinecke, Sasikanth Avancha +3
At the heart of deep learning training and inferencing are computationally intensive primitives such as convolutions which form the building blocks of deep neural networks. Researc…