TBEM: Testing-Based GPU-Memory Consumption Estimation for Deep Learning

Author:

Liu Haiyi1,Liu Shaoying1ORCID,Wen Chenglong2,Wong W. Eric3ORCID

Affiliation:

1. Department of Advanced Science and Engineering, Hiroshima University, Hiroshima, Japan

2. Microsoft Software Technology Center Asia, Microsoft, Suzhou, China

3. Department of Computer Science, The University of Texas at Dallas, Richardson, TX, USA

Funder

Research Organization of Information and Systems (ROSI), National Institute of Informatics (NII) Open Collaborative Research 2021

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Reference26 articles.

1. SOFL: a formal engineering methodology for industrial applications

2. Automatic Test Case and Test Oracle Generation based on Functional Scenarios in Formal Specifications for Conformance Testing

3. Formal Specification for Deep Neural Networks

4. A formalization of robustness for deep neural networks;dreossi;arXiv 1903 10033,2019

5. Training deep nets with sublinear memory cost;chen;arXiv 1604 06174,2016

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