HLRS provides our users with access to and assistance in using many of the most commonly used application software packages in the area of high-performance computer simulations for science and engineering. We have also developed powerful software for immersive, 3D data visualization, and support the most popular frameworks for machine learning and artificial intelligence. For users developing their own codes, we also offer software development tools, compilers, and libraries that make it possible to run algorithms on our systems.
HLRS provides our users access to a wide range of essential software packages for research in computational fluid dynamics, computational structural mechanics, molecular dynamics, computational chemistry, astrophysics, and other fields. These include both open source (community) and ISV (commercial) application packages. Visit the HLRS Platforms Wiki to learn more
To support users who bring their own code, HLRS's computing platforms are installed with software development tools, compilers, and libraries that make it possible to run user-developed algorithms on our systems. These include integrated development environments, MPI, communication libraries, debuggers, tools for performance analysis, compilers, numerical libraries, visualization tools, and storage formats. Visit the HLRS Platforms Wiki to learn more
HLRS has developed several custom software packages, including COVISE and Vistle, that make it possible to convert data generated by our high-performance computing systems into virtual reality and augmented reality applications, including in the HLRS CAVE. In addition, HLRS has created software called OddLOT that makes it possible to test autonomous driving and advanced driver assistance systems in virtual reality.
HLRS systems accommodate the latest versions of frequently used programming languages for machine learning and AI, including Apache Spark, TensorFlow, and PyTorch. HLRS also makes it possible for users to port their own software to our systems using PIP (Python), Anaconda, and container frameworks, and can provide advice on the development of hybrid workflows combining AI and high-performance computing. Learn more about Artificial Intelligence and Data Analytics.
As a participant in the SEQUOIA project, HLRS is currently involved in research aimed at (1) designing and developing applications and algorithms to demonstrate the effectiveness of solutions based on quantum computing; (2) implementing a software library to ease access to quantum systems by introducing standards for data formats and interfaces; and (3) defining an engineering model that describes best practices when developing applications for quantum computing.
HLRS staff is available to assist you if you have questions about software for specific domains. Visit our Key Contacts page for more information.
Are you new to high-performance computing? Our comprehensive training program can help you develop the skills to program and operate highly parallel computing clusters confidently and effectively.
