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High Performance Computing is a rapidly changing field which requires constant research. At any given time ARC is researching multiple new technologies and methodologies in order to create increasingly efficient and user-friendly workflows, and to provide the computing power necessary for the wide array of scientific computing workloads within the USGS.

Computer Node
Internal view of a compute node.(Credit: Jeff Falgout. Public domain.)

Current Research Initiatives

Accelerator Technologies: Accelerator use has become a standard in modern supercomputing. How can GPUs or other coprocessors be used to benefit scientific research?

Machine Learning: Over the past few years machine learning and deep learning methodologies have taken off and been successful in a variety disciplines, but how can these techniques benefit USGS science?

Emerging Processor Technologies and Software Ecosystems: As new technologies become available, what are the cost savings vs. productivity trade-offs for scientific use cases?

High Performance Data Analytics (HPDA): How can ARC take advantage of the confluence of HPC and Big Data analytics?

Data Management: How can we streamline data management workflows for HPC research? What are the best practices for data movement (transfer) and storage?

Containers: Can containers be used to package entire scientific workflows, software and libraries, and even data? How will they affect reproducibility and portability?