Faster Neural Network Training with Approximate Tensor Operations. - Menachem Adelman; Mark Silberstein (CoRR, 2018)

Faster Neural Network Training with Approximate Tensor Operations. - Menachem Adelman; Kfir Y. Levy; Ido Hakimi; Mark Silberstein (NeurIPS, 2021)

Tensor processing primitives: a programming abstraction for efficiency and portability in deep learning workloads. - Evangelos Georganas; Dhiraj D. Kalamkar; Sasikanth Avancha; Menachem Adelman; Cristina Anderson; Alexander Breuer; Jeremy Bruestle; Narendra Chaudhary; Abhisek Kundu; Denise Kutnick; Frank Laub; Md. Vasimuddin; et al. (SC, 2021)

Tensor Processing Primitives: A Programming Abstraction for Efficiency and Portability in Deep Learning Workloads. - Evangelos Georganas; Dhiraj D. Kalamkar; Sasikanth Avancha; Menachem Adelman; Cristina Anderson; Alexander Breuer; Narendra Chaudhary; Abhisek Kundu; Md. Vasimuddin; Sanchit Misra; Ramanarayan Mohanty; Hans Pabst; et al. (CoRR, 2021)

Efficient and Generic 1D Dilated Convolution Layer for Deep Learning. - Narendra Chaudhary; Sanchit Misra; Dhiraj D. Kalamkar; Alexander Heinecke; Evangelos Georganas; Barukh Ziv; Menachem Adelman; Bharat Kaul (CoRR, 2021)

Accelerating Deep Learning based Identification of Chromatin Accessibility from noisy ATAC-seq Data. - Narendra Chaudhary; Sanchit Misra; Dhiraj D. Kalamkar; Alexander Heinecke; Evangelos Georganas; Barukh Ziv; Menachem Adelman; Bharat Kaul (IPDPS Workshops, 2022)

Tensor Processing Primitives: A Programming Abstraction for Efficiency and Portability in Deep Learning and HPC Workloads. - Evangelos Georganas; Dhiraj D. Kalamkar; Sasikanth Avancha; Menachem Adelman; Deepti Aggarwal; Cristina Anderson; Alexander Breuer; Jeremy Bruestle; Narendra Chaudhary; Abhisek Kundu; Denise Kutnick; Frank Laub; et al. (Frontiers Appl. Math. Stat., 2022)