Abstract is missing.
- Understanding Scalability and Fine-Grain Parallelism of Synchronous Data Parallel TrainingJiali Li, Bogdan Nicolae, Justin Wozniak, George Bosilca. 1-8 [doi]
- Fine-Grained Exploitation of Mixed Precision for Faster CNN TrainingJeremy T. Johnston, Steven R. Young, Catherine D. Schuman, Junghoon Chae, Don D. March, Robert M. Patton, Thomas E. Potok. 9-18 [doi]
- Metaoptimization on a Distributed System for Deep Reinforcement LearningGreg Heinrich, Iuri Frosio. 19-30 [doi]
- Scheduling Optimization of Parallel Linear Algebra Algorithms Using Supervised LearningGabriel Laberge, Shahrzad Shirzad, Patrick Diehl, Hartmut Kaiser, Serge Prudhomme, Adrian S. Lemoine. 31-43 [doi]
- Parallel Data-Local Training for Optimizing Word2Vec Embeddings for Word and Graph EmbeddingsGordon E. Moon, Denis Newman-Griffis, Jinsung Kim, Aravind Sukumaran-Rajam, Eric Fosler-Lussier, P. Sadayappan. 44-55 [doi]
- Scalable Hyperparameter Optimization with Lazy Gaussian ProcessesRaju Ram, Sabine Müller, Franz-Josef Pfreundt, Nicolas R. Gauger, Janis Keuper. 56-65 [doi]
- GradVis: Visualization and Second Order Analysis of Optimization Surfaces during the Training of Deep Neural NetworksAvraam Chatzimichailidis, Janis Keuper, Franz-Josef Pfreundt, Nicolas R. Gauger. 66-74 [doi]
- DisCo: Physics-Based Unsupervised Discovery of Coherent Structures in Spatiotemporal SystemsAdam Rupe, Prabhat, James P. Crutchfield, Nalini Kumar, Vladislav Epifanov, Karthik Kashinath, Oleksandr Pavlyk, Frank Schlimbach, Mostofa Patwary, Sergey Maidanov, Victor W. Lee. 75-87 [doi]