Recipient Organization
UTAH STATE UNIVERSITY
(N/A)
LOGAN,UT 84322
Performing Department
Agricultural Experiment Station
Non Technical Summary
The project goal is to extend the use and application of high performance computing to the agricultural research community. The Center for High Performance Computing at Utah State University (HPC@USU) addresses this goal by developing an integrated, easy to use computational infrastructure. This initiative is in concert with the Agricultural, Rural Development, Food and Drug Administration, and Related Agencies Appropriations Act of 2010, as well with the President's Information Technology Advisory Committee (PITAC) report (Committee, 2005) and the recently passed High Performance Computing (HPC) Revitalization Act and addresses the critical needs for high performance computing education and resources on the local, state and national level. Through this program, the high performance computing resources at HPC@USU will be expanded to meet new challenges related to producing, storing, processing and archiving substantially larger datasets. Agricultural researchers often require a variety of externally and internally generated datasets to both build their research process as well as validate their results. The ability to store and process a greater variety of larger datasets represents an essential infrastructural improvement for HPC@USU that will allow research simulations to achieve a new level of detail and confidence. In addition, a great research emphasis will be on directly educating, through hands-on computational research, a PhD student working with Dr. Jin to learn specifics of computational research as applied to snowpack and drought research.
Animal Health Component
(N/A)
Research Effort Categories
Basic
100%
Applied
(N/A)
Developmental
(N/A)
Goals / Objectives
1. Quantify the Relationship Between Snowpack and Drought in the Western United States using Regional Climate Modeling. In this work we will investigate how climate change affects snowpack and drought in the Western United States. To achieve this goal, the relationships among climate change, snowpack, and drought will be qualitatively assessed using historical data. Both field observations and numerical modeling results will be applied in this investigation. This study will provide insight into how climate change affects past and future snowpack, drought occurrence, and water supply. It will also provide decision-makers with better data upon which to make informed decisions. 2. Enhanced Capacity And Capabilities for Cluster Attached Storage. To accommodate the large and varied datasets that projects such as the Regional Climate Modeling project require, we will build a scale-out network attached storage (NAS) solution that will expand our current storage capacity, as well as provide our high performance computing environment with significant new storage capabilities. Features previously considered high-end storage capabilities such as filesystem parallelization, near-linear scalability, non-disruptive maintenance, enhanced availability through advanced RAID and data replication for offsite data storage archival, are now necessary tools for effectively managing large research datasets. Despite the premium nature of these features, the price per terabyte must be less than or equal to what we have historically paid for low-end storage. Recent vendor pricing shows that this is possible. Therefore, HPC@USU will build and grow a scalable-NAS storage solution with the appropriate balance of price, performance, scalability and availability that will allow us to maintain larger datasets for the life of a project as well as archive datasets that have value beyond the life of a project.
Project Methods
1. The advanced regional climate model Weather Research and Forecasting (WRF) developed by the National Center for Atmospheric Research (NCAR) will be used for this investigation. We recently coupled the Community Land Model version 3 (CLM3) with WRF (WRFC) to improve the simulations of snow and related land surface variables as well as heat and water flux exchanges between the land surface and atmosphere. The advanced CLM3 has been shown to be accurate in describing snow, soil, and vegetation processes for global and regional applications. CLM3 includes a 5-layer snow scheme, a 10-layer soil scheme, and a single layer vegetation scheme. Solid ice and liquid water are described in the snowpack as prognostic variables. A sophisticated snow compaction scheme is used to calculate the height and density of snow, where snow density is a critical variable for describing water and heat transfer within the snowpack. The model physically describes frozen soil processes and their impact on soil properties. A 20 km resolution domain will be set within WRFC; this domain covers the entire WUS that is the focus of this study. WRFC will be configured with 28 vertical sigma layers from the surface to the 50 hPa level. In order to properly represent the planetary boundary layer processes, the vertical layers will be closely spaced near the surface and coarsely spaced in the upper atmosphere. In addition, the 6 hr 2.5o x 2.5o National Centers for Environmental Predictions/ Department of Energy Reanalysis (NCEP 2) data will drive WRFC to perform historical simulations for the period September 1, 1979 to December 31, 2007. 2. HPC@USU will build and grow a scale-out NAS storage solution to replace and increase our existing general storage pool. We expect to initially build a 120TB general storage pool and then grow the solution from there. This is the best way for us to meet the challenge of processing, managing and archiving the mountain of research data that is beyond our current capabilities. One core feature of this solution will be filesystem parallelization via a protocol known as Parallel NFS (pNFS). The pNFS protocol is part of the NFS v4.1 standard, and it is an important consideration for compatibility reasons. While moving away from stand-alone NFS towards a scale-out NAS solution, compatibility and ease of migration is a principle concern and is largely addressed by the pNFS protocol. However, there are other important considerations that must be addressed as well. The appropriate balance of performance, scalability, availability, and price also need to be considered. The scale-out NAS solution that best balances these considerations is based on the Panasas ActiveStore Series 7 product that offers many high-end features in an entry-level scale-out NAS solution.