Rapid and disruptive changes in computing hardware combined with innovative machine learning (ML) and Artificial Intelligence (AI) applications are creating new opportunities and new challenges for biological and environmental system science. Mid-range, high-performance computing systems have an important role in providing the research community with hardware that meets their diverse computing needs including: the GPUs that are essential for running advanced ML algorithms, which require significant computational power; and the memory and data storage capacity to facilitate AI integration of diverse data sources, such as remote sensing, molecular data, and model simulations. DOE BER supported compute systems enable the innovative ML and AI approaches that will discover patterns and insights that are critical to advance biological and environmental research.

The Computing Infrastructure (CI) working group strives to connect the research community with computing resources, introduce researchers to the advanced tools and support available to them, and to coordinate with the other working groups to keep up with emerging computing requirements and demonstrate workflows for new data streams.

Tahoma and Compass are two computing systems that combine mid-range CPU-based computing with GPU accelerated nodes to provide the research community with the resources to meet their diverse computing needs. These systems are maintained by the Environmental Molecular Sciences Laboratory (EMSL) at the Pacific Northwest National Laboratory (PNNL) with funding from DOE BER.

Tahoma is available through the EMSL User Program. The Compass computer is available to researchers working on coastal and terrestrial-aquatic systems via online request.

Computing Infrastructure lead

Lee Ann McCue
LeeAnn.McCue@pnnl.gov
Pacific Northwest National Laboratory

Want to contribute? Ask the lead to join the Google Group: ess-community-ci@googlegroups.com