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Scaling Deep Learning Workloads: NVIDIA DGX-1/Pascal and Intel Knights Landing.

, , , , , and . IPDPS Workshops, page 399-408. IEEE Computer Society, (2017)

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Multimodal Deep Neural Networks using Both Engineered and Learned Representations for Biodegradability Prediction., , , , and . CoRR, (2018)Special issue on programming models, systems software, and tools for High-End Computing., , and . Parallel Comput., 39 (12): 751-752 (2013)Special Issue on Programming Models and Systems Software Support for High-End Computing Applications., and . Int. J. High Perform. Comput. Appl., 25 (2): 135-136 (2011)Using Rule-Based Labels for Weak Supervised Learning: A ChemNet for Transferable Chemical Property Prediction., , , and . KDD, page 302-310. ACM, (2018)Guest Editors' introduction., , and . J. Supercomput., 63 (2): 323-325 (2013)Designing energy efficient communication runtime systems: a view from PGAS models., , , , , , and . J. Supercomput., 63 (3): 691-709 (2013)Diagnosing the causes and severity of one-sided message contention., , , , , and . PPoPP, page 130-139. ACM, (2015)Designing Energy Efficient Communication Runtime Systems for Data Centric Programming Models., , , , , , and . GreenCom/CPSCom, page 229-236. IEEE Computer Society, (2010)ParLearning 2018 Invited Talk 1.. IPDPS Workshops, page 854. IEEE Computer Society, (2018)Introduction to GraML 2018., , , , and . IPDPS Workshops, page 1166-1167. IEEE Computer Society, (2018)