DLVM: A modern compiler infrastructure for deep learning systems

Preprint English OPEN
Wei, Richard; Schwartz, Lane; Adve, Vikram;
(2017)
  • Subject: Computer Science - Programming Languages | Computer Science - Mathematical Software | Computer Science - Learning
    acm: Software_PROGRAMMINGLANGUAGES

Deep learning software demands reliability and performance. However, many of the existing deep learning frameworks are software libraries that act as an unsafe DSL in Python and a computation graph interpreter. We present DLVM, a design and implementation of a compiler ... View more
  • References (17)
    17 references, page 1 of 2

    Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Gregory S. Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian J. Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Józefowicz, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dan Mané, Rajat Monga, Sherry Moore, Derek Gordon Murray, Chris Olah, Mike Schuster, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul A. Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda B. Viégas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, and Xiaoqiang Zheng. TensorFlow: Large-scale machine learning on heterogeneous distributed systems. CoRR, abs/1603.04467, 2016. URL http://arxiv.org/abs/1603.04467.

    Tianqi Chen, Mu Li, Yutian Li, Min Lin, Naiyan Wang, Minjie Wang, Tianjun Xiao, Bing Xu, Chiyuan Zhang, and Zheng Zhang. Mxnet: A flexible and efficient machine learning library for heterogeneous distributed systems. CoRR, abs/1512.01274, 2015. URL http://arxiv.org/ abs/1512.01274.

    Tianqi Chen, Thierry Moreau, Ziheng Jiang, and Haichen Shen. TVM: An end to end IR stack for deploying deep learning workloads on hardware platforms. http://tvmlang.org/2017/ 08/17/tvm-release-announcement.html, 2017.

    Ronan Collobert, Koray Kavukcuoglu, and Clément Farabet. Torch7: A Matlab-like environment for machine learning. In NIPS Big Learning Workshop: Algorithms, Systems, and Tools for Learning at Scale, December 2011.

    Ian Goodfellow, Yoshua Bengio, and Aaron Courville. Deep Learning. MIT Press, 2016. http: //www.deeplearningbook.org.

    Google Brain Team. Eager Execution: An imperative, define-by-run interface to TensorFlow. 2017. URL https://research.googleblog.com/2017/10/ eager-execution-imperative-define-by.html.

    Joe Groff and Chris Lattner. Swift's High-Level IR: A Case Study of Complementing LLVM IR with Language-Specific Optimization. 2015 LLVM Developers' Meeting, 2015. URL http: //llvm.org/devmtg/2015-10/slides/GroffLattner-SILHighLevelIR.pdf.

    Norman P. Jouppi, Cliff Young, Nishant Patil, David Patterson, Gaurav Agrawal, Raminder Bajwa, Sarah Bates, Suresh Bhatia, Nan Boden, Al Borchers, Rick Boyle, Pierre-luc Cantin, Clifford Chao, Chris Clark, Jeremy Coriell, Mike Daley, Matt Dau, Jeffrey Dean, Ben Gelb, Tara Vazir Ghaemmaghami, Rajendra Gottipati, William Gulland, Robert Hagmann, Richard C. Ho, Doug Hogberg, John Hu, Robert Hundt, Dan Hurt, Julian Ibarz, Aaron Jaffey, Alek Jaworski, Alexander Kaplan, Harshit Khaitan, Andy Koch, Naveen Kumar, Steve Lacy, James Laudon, James Law, Diemthu Le, Chris Leary, Zhuyuan Liu, Kyle Lucke, Alan Lundin, Gordon MacKean, Adriana Maggiore, Maire Mahony, Kieran Miller, Rahul Nagarajan, Ravi Narayanaswami, Ray Ni, Kathy Nix, Thomas Norrie, Mark Omernick, Narayana Penukonda, Andy Phelps, Jonathan Ross, Amir Salek, Emad Samadiani, Chris Severn, Gregory Sizikov, Matthew Snelham, Jed Souter, Dan Steinberg, Andy Swing, Mercedes Tan, Gregory Thorson, Bo Tian, Horia Toma, Erick Tuttle, Vijay Vasudevan, Richard Walter, Walter Wang, Eric Wilcox, and Doe Hyun Yoon. In-datacenter performance analysis of a tensor processing unit. CoRR, abs/1704.04760, 2017. URL http: //arxiv.org/abs/1704.04760.

    Chris Lattner and Vikram Adve. LLVM: A Compilation Framework for Lifelong Program Analysis & Transformation. In Proceedings of the 2004 International Symposium on Code Generation and Optimization (CGO'04), Palo Alto, California, Mar 2004.

    Chris Leary and Todd Wang. XLA: TensorFlow, compiled! TensorFlow Dev Summit 2017, February 2017.

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