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NASA Advanced Supercomputing (NAS) Division World-class modeling, simulation, and supercomputing in support of the NASA mission

Data Analytics

Machine learning, deep learning, and artificial intelligence have become essential tools for handling and gaining insight from the enormous amounts of data generated via high-performance computing, modern modeling and simulation, and instrument technology.

The NAS Data Analytics team works with researchers supporting NASA missions who are turning to these tools to help analyze their large datasets and to solve problems that would be too time-consuming or resource-intensive to solve using traditional physics-based or statistical modeling approaches. The team helps scientists and engineers make the most effective use of data science and machine learning resources and services provided by the High-End Computing Capability (HECC) Project, including:

  • Data science environments with basic machine learning packages.
  • Container-based solutions for building machine learning software stacks for use on HECC resources.
  • Machine learning models, software libraries, and custom-built neural networks.
  • Best practices for running jobs on graphics processing unit (GPU) nodes.

The Data Analytics team is currently working with NASA researchers on a number of pilot projects. For example, the NAS team built and trained a neural network to accurately interpret sensor data that will be used for monitoring cabin air on the International Space Station.