<?xml version="1.0" encoding="US-ASCII"?>
<dblp>
<article key="journals/corr/abs-2104-05755" publtype="informal" mdate="2024-04-08">
<author>Evangelos Georganas</author>
<author>Dhiraj D. Kalamkar</author>
<author>Sasikanth Avancha</author>
<author>Menachem Adelman</author>
<author>Cristina Anderson</author>
<author>Alexander Breuer</author>
<author>Narendra Chaudhary</author>
<author>Abhisek Kundu</author>
<author>Md. Vasimuddin</author>
<author>Sanchit Misra</author>
<author>Ramanarayan Mohanty</author>
<author>Hans Pabst</author>
<author>Barukh Ziv</author>
<author>Alexander Heinecke</author>
<title>Tensor Processing Primitives: A Programming Abstraction for Efficiency and Portability in Deep Learning Workloads.</title>
<year>2021</year>
<volume>abs/2104.05755</volume>
<journal>CoRR</journal>
<ee type="oa">https://arxiv.org/abs/2104.05755</ee>
<url>db/journals/corr/corr2104.html#abs-2104-05755</url>
</article></dblp>
