This page will contain presentations, publications, and reports created by the Deep Learning MRI.
PUBLICLY RELEASED SOFTWARE
- [Open Source Framework] Performance tuning framework for TensorFlow.
- [Open Source Tool] TensorFlow Runtime Tracing Metadata Visualization.
- [Contribution to an open source tool] Expanding tracing capability of TensorFlow.
- [Dataset] Deep Learning I/O benchmark.
- Volodymyr Kindratenko, Dawei Mu, Yan Zhan, John Maloney, Sayed Hadi Hashemi, Benjamin Rabe, Ke Xu, Roy Campbell, Jian Peng, and William Gropp. 2020. HAL: Computer System for Scalable Deep Learning. InPractice and Experience in Advanced Research Computing (PEARC ’20), July 26–30, 2020, Portland, OR, USA. ACM, New York, NY, USA, 15 pages. https://doi.org/10.1145/3311790.3396649
- Venkatakrishnan, Ramshankar, Ashish Misra, and Volodymyr Kindratenko. “High-Level Synthesis-Based Approach for Accelerating Scientific Codes on FPGAs.” Computing in Science & Engineering 22.4 (2020): 104-109. https://doi.org/10.1109/MCSE.2020.2996072
- Misra, Ashish, and Volodymyr Kindratenko. “HLS-Based Acceleration Framework for Deep Convolutional Neural Networks.” International Symposium on Applied Reconfigurable Computing. Springer, Cham, 2020. https://doi.org/10.1007/978-3-030-44534-8_17
- S. Hashemi, P. Rausch, B. Rabe, K. Chou, S. Liu, V. Kindratenko, R. Campbell, “tensorflow-tracing: A Performance Tuning Framework for Production,” In Proc. 2019 USENIX Conference on Operational Machine Learning (OpML’19), 2019.
- S. H. Hashemi, S. Abdu Jyothi, R. H. Campbell, “TicTac: Improving Distributed Deep Learning With Communication Scheduling,” SysML Conference 2019.
- S. H. Hashemi, S. Abdu Jyothi, R. H. Campbell, “On Importance of Execution Ordering in Graph-Based Distributed Machine Learning Systems,” SysML Conference 2018.
PRESENTATIONS AND POSTERS
- V. Kindratenko, “POWER9 AI Cluster at NCSA” University Power Systems HPC/AI User Meeting, December 21, 2019, SC19 – Denver, CO.
- S. H. Hashemi, S. Abdu Jyothi, and R. H. Campbell, “Network Efficiency through Model-Awareness in Distributed Machine Learning Systems,” NSDI ’18, Seattle, WA.
- S. H. Hashemi and R. H. Campbell, “Making a Case for Timed RPCs in Iterative Systems,” OSDI ’18, San Diego, CA.
- S. H. Hashemi, B. Rabe, V. Kindratenko, “Building a Scalable Deep Learning Platform,” University Power Systems HPC/AI User Meeting, December 15, 2018, SC18 – Dallas, TX.