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Fredrik Kjolstad, Shoaib Kamil, Stephen Chou, David Lugato and Saman Amarasinghe
  taco: A Tool to Generate Tensor Algebra Kernels

ASE, October 2017 (tools paper).

Abstract

Tensor algebra is an increasingly important computational abstraction that is used in data analytics, machine learning, engineering and the physical sciences. However, the number of tensor expressions is unbounded, which makes it hard to develop and optimize libraries. Furthermore, the tensors are often sparse (most components are zero) which means the code has to traverse compressed formats. To support programmers, we have developed taco, a code generation tool that generates dense, sparse and mixed kernels from tensor algebra expressions. This paper describes the taco web and command-line tools, and discusses the benefits of a code generator over a traditional library approach.

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BibTeX

@inproceedings{kjolstad2017tool,
  title={taco: A Tool to Generate Tensor Algebra Kernels},
  author={Kjolstad, Fredrik and Chou, Stephen and Lugato, David and Kamil, Shoaib and Amarasinghe, Saman},
  booktitle={Automated Software Engineering (ASE), 2017 32th IEEE/ACM International Conference on},
  year={2017},
  month={October},
  organization={IEEE}
  }