Location: National Programs
Project Number: 0500-00093-001-009-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: Sep 29, 2024
End Date: Sep 28, 2026
Objective:
Modern scientific computing tools and methods, including high-performance computing (HPC), have transformed agricultural research. However, successful application of these rapidly changing technologies to scientific research requires specialized training in a variety of skill areas. The purpose of this Non-Assistance Cooperative Agreement (NACA) is to support ongoing cooperation and collaboration between the United States Department of Agriculture (USDA) Agricultural Research Service (ARS) and Iowa State University (ISU) for the development of scientific computing and HPC training and research support as part of ARS’s Scientific Computing Initiative (SCINet). SCINet is an effort by ARS to enhance the USDA’s research capacity by providing scientists with access to HPC clusters, cloud computing, a high-capacity data storage environment, advanced networking for data transfer, and training in scientific computing.
Approach:
ARS has deep scientific expertise across a wide spectrum of agricultural research domains, and ARS scientists are pursuing numerous research questions that can benefit from modern scientific computing techniques. ARS also has the computing infrastructure to support modern scientific computing methods, including multiple HPC clusters. The Cooperator has major research programs in agriculture and natural resources and extensive expertise in leveraging HPC and modern computing and data analysis methods for scientific research. This NACA will support the collaborative development of scientific computing training and support materials applicable to SCINet computing resources. Training materials will include several modes of instruction for asynchronous and synchronous learning, including instructional tutorials organized into an online “workbook”, training workshops, live and pre-recorded demonstrations, and open-ended question and answer sessions. These training materials are designed to better equip ARS researchers with the knowledge and skills needed to apply the complexities of HPC environments efficiently to their research. There is currently a particular need for bioinformatics-related training resources at ARS, so the collaborative work supported by this agreement will primarily focus on, but not necessarily be limited to, bioinformatics methods and the foundational computing skills needed to apply them.
