STACK Gallery
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Access Token API-key Authentication AVHRR C3S Cluster Core API CUDA cuDF cuML Dask Deep Learning DestineLab Digital Twin earthkit ECMWF EODAG ERA5 GFM GPU HDA Hook HTTP requests Machine Learning Metop OLCI pyaviso PyTorch Queryables RAPIDS ROI satpy scikit-learn Sentinel-2 Sentinel-3 SEVIRI STAC STACK Storage TensorFlow Time Series Token Workflow XGBoost
STACK Service Dask
This notebook introduces authentication and multi-cluster management using the DEDL Stack client with OIDC, enabling users to securely spawn, monitor, and scale Dask clusters across Central and LUMI locations within the DestinE Data Lake.
This notebook introduces authentication and multi-cluster management using the DEDL Stack client with OIDC, enabling users to securely spawn, monitor, and scale Dask clusters across Central and LUMI locations within the DestinE Data Lake.
STACKDaskGFM
View NotebookSTACK service - Dask 101
This notebook introduces Dask's core APIs and demonstrates how to use them for scalable, parallel, and distributed data processing, culminating in deploying and interacting with a Dask cluster on the DestinE Data Lake STACK service.
This notebook introduces Dask's core APIs and demonstrates how to use them for scalable, parallel, and distributed data processing, culminating in deploying and interacting with a Dask cluster on the DestinE Data Lake STACK service.
STACKDaskCluster
View NotebookSTACK service - Python Client Dask
This notebook demonstrates how to use the DEDL Stack Python client to authenticate, manage, and execute parallel, multi-cloud Dask computations on distributed datasets stored across Central Site and LUMI bridge.
This notebook demonstrates how to use the DEDL Stack Python client to authenticate, manage, and execute parallel, multi-cloud Dask computations on distributed datasets stored across Central Site and LUMI bridge.
STACKDaskGFM
View Notebook
Deep Learning example for Sentinel-2
Land cover classification on Sentinel-2 images with CNN. Used ResNet-18 with transfer learning from ImageNet
Land cover classification on Sentinel-2 images with CNN. Used ResNet-18 with transfer learning from ImageNet
Deep LearningSentinel-2GPU
View NotebookPyTorch GPU example
CUDA checks, benchmarks, and toy training. GPU vs CPU comparison.
CUDA checks, benchmarks, and toy training. GPU vs CPU comparison.
PyTorchCUDADeep LearningGPU
View NotebookRAPIDS GPU acceleration
cuDF and cuML benchmarks. GPU vs CPU comparison.
cuDF and cuML benchmarks. GPU vs CPU comparison.
RAPIDScuDFcuMLGPU
View Notebookscikit-learn vs cuML
scikit-learn vs cuML comparison on basic ML methods.
scikit-learn vs cuML comparison on basic ML methods.
scikit-learncuMLMachine LearningGPU
View NotebookTensorFlow GPU example
Device checks, benchmarks (GPU vs CPU), and CNN training.
Device checks, benchmarks (GPU vs CPU), and CNN training.
TensorFlowCUDADeep LearningGPU
View NotebookXGBoost GPU training
CPU and CUDA training comparison for decision tree.
CPU and CUDA training comparison for decision tree.
XGBoostMachine LearningCUDAGPU
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