Scientific Computing

We use our expertise in compiler and language technology to build accessible tools for scientific users.

Robust science via computing requires reliable, trustworthy tools to produce solid results and protect data integrity. Computers have become critical to scientific discovery: experiment design, execution, and data analysis rely on scientific computing in contexts ranging from small table-top experiments to world-class experimental facilities like the CERN LHC. It is therefore important that scientific users be given increased assurance that their computational tools produce reliable, trustworthy results, and protect the integrity of their data. Furthermore, with computing becoming a commonplace tool in the laboratory, it is very important to make computation as accessible to domain scientists as traditional lab instruments.

Working towards these ends, research and development at Galois in the scientific computing area is focused on these three topics:

  • Confidence in Scientific Computing: We provide practitioners with high assurance computational tools and automated processes designed to prevent human mistakes and probe the quality and integrity of the computational results.
  • Accessibility of Complex Computational Resources to Domain Scientists: We build tools to help scientific users take advantage of novel computational methods without exposing the underlying computing system, allowing the users to focus on the science.
  • Modeling and Simulation: We offer optimization and design services for modeling and simulation applications which can significantly affect performance and maintenance costs, based on our unique combination of expertise in computational tools and diverse experience working with domain scientists.
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Contact Scientific Computing

Connect directly with our Scientific Computing team to learn more about our work, process, and partnerships. We try to respond to general inquiries within one business day; for inquiries sent to a team lead, please allow more time for a reply.

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