A browser-based geospatial data discovery and collection interface for selecting an area of interest, checking satellite scene availability, configuring collection parameters, and submitting GeoHarmonizer collection jobs to HPC resources through Tapis.
Area of Interest
What Version 1.2.0 Adds
- This dataset captures both tabular metadata and graph representations from deep learning training workflows, extracted via TensorFlow's XLA compiler.
What I-SAW is
Available operations
TapisUI provides a research oriented frontend to interact with Tapis and tenant components. In this case, the ICICLE extension extends TapisUI with custom branding
The GNN Food Flow Portal is a Streamlit web app for exploring county-level U.S. food-flow predictions from the GNN FoodFlow Model. Version 1.2.0 includes the original parallel SCTG-specific model exploration workflow plus a new multi-task GNN what-if portal for one-to-one and one-to-many county scenario analysis.
A dataset designed to support AI-driven resource estimation like runtime prediction to support HPC scheduling optimization by leveraging compiler-level High-Level Optimizer (HLO) graph features and deep learning workload metadata.
Run Earth Data Hub Locally
Run the Portal Locally
How to Predict Training Time Using Metadata
Build a production bundle
The pipeline file (operations.json)
View the main TapisUI wiki to learn how to deploy and test TapisUI extensions locally.
A public-facing web portal for I-SAW: Infrastructure for Sensing and Analytics on Wildlife — a plug-and-play, edge-networked wildlife sensing platform built for K-12 camps, citizen scientists, and field researchers. The portal presents the project vision, an interactive "Smart Honeypot" data sandbox with analytics dashboards, and an onboarding hub where visitors can download a deployment script, generate a device config.json, or request a prebuilt field kit.
A browser-based OpenCV pipeline builder: build an image pre-processing
An AI-driven educational framework that integrates automated curriculum generation with an end-to-end computer vision pipeline, enabling learning for high school and undergraduate students combining domain agnostic datasets with machine learning and AI concepts.
This tapis ui extension enables additional icicle specific branding and tabs on tapisui.
Open Earth Data Hub
Explore Parallel Model Food Flows
Getting Started with the HLO Feature Dataset
Run the portal locally
Build a pipeline (editor)
This documentation goes over how to use Smart Curriculum Designer, the machine learning and AI curriculum generator. The application itself enables educators to generate models, content, exercises, and solutions, weaving the domain/dataset specified by the educator.