Optimizing data-intensive computations in existing libraries with split annotations-Reference-Cited by-同舟云学术

Optimizing data-intensive computations in existing libraries with split annotations

Published:2019-10-27 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 27th ACM Symposium on Operating Systems Principles
language:
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Author:

Palkar Shoumik¹,Zaharia Matei¹

Affiliation:

1. Stanford University

Funder

NSF

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3341301.3359652

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3. 2017. XLA: TensorFlow Compiled! (TensorFlow Dev Summit 2017). https://www.youtube.com/watch?v=kAOanJczHA0&feature=youtu.be&t=41m46s. 2017. XLA: TensorFlow Compiled! (TensorFlow Dev Summit 2017). https://www.youtube.com/watch?v=kAOanJczHA0&feature=youtu.be&t=41m46s.

4. 2018. Dask. https://dask.pydata.org. 2018. Dask. https://dask.pydata.org.

5. 2018. Intel Math Kernel Library. https://software.intel.com/en-us/mkl. 2018. Intel Math Kernel Library. https://software.intel.com/en-us/mkl.

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