Global Computing Lab's repositories
SOMOSPIE
SOMOSPIE (Soil Moisture Spatial Inference Engine) consists of a Jupyter Notebook and a suite of machine learning methods to process inputs of available coarse-grained soil moisture data at its native spatial resolution. Features include the selection of a geographic region of interest, prediction of missing values across the entire region of interest (i.e., gap-filling), analysis of generated fine-grained predictions, and visualization of both predictions and analyses.
NASMo-TiAM
Workflow for Generating North America Soil Moisture at 250m Dataset Derived From Time-specific Adaptable Machine Learning Models
DockingAtHome-Website
Source code for the Docking@Home BOINC project web page.
benchpark
An open collaborative repository for reproducible specifications of HPC benchmarks and cross site benchmarking environments
flux-docs
Documentation for the Flux-Framework
flux-framework-tutorials
Tutorial slides and materials
flux-radiuss-tutorial-2023
Files for the Flux RADIUSS Tutorials
llnl-hatchet
Graph-indexed Pandas DataFrames for analyzing hierarchical performance data
PerfFlowAspect
An Aspect Oriented Programming (AOP)-based tool to analyze cross-cutting performance concerns of composite science workflows.