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Machine learning libraries such as TensorFlow and PyTorch simplify modelimplementation. However, researchers are still required to perform anon-trivial amount of manual tasks such as GPU allocation, training statustracking, and comparison of models with different hyperparameter settings. Wepropose a system to handle these tasks and help researchers focus on models. Wepresent the requirements of the system based on a collection of discussionsfrom an online study group comprising 25k members. These include automatic GPUallocation, learning status visualization, handling model parameter snapshotsas well as hyperparameter modification during learning, and comparison ofperformance metrics between models via a leaderboard. We describe the systemarchitecture that fulfills these requirements and present a proof-of-conceptimplementation, NAVER Smart Machine Learning (NSML). We test the system andconfirm substantial efficiency improvements for model development.

NSML: A Machine Learning Platform That Enables You to Focus on Your Models