All software
Kernel Tuner
Kernel Tuner greatly simplifies the development of highly-optimized and auto-tuned CUDA, OpenCL, and C code, supporting many advanced use-cases and optimization strategies that speed up the auto-tuning process.
- Big data
- GPU
- High performance computing
- + 3
- Python
- Cuda
FAIR Data Point
RESTful web service that enables data owners to expose their data sets using rich machine-readable metadata.
- Big data
- Inter-operability & linked data
- Python
- Makefile
- Dockerfile
Parcels
Parcels (Probably A Really Computationally Efficient Lagrangian Simulator) is a set of Python classes and methods to create customisable particle tracking simulations using output from Ocean Circulation models. Parcels can be used to track passive and active particulates such as plastic and fish.
- lagrangian-ocean-modelling
- ocean-circulation-models
- particles
- Python
- C
Paired omics data platform
If you do metabolomics experiments with mass spectra and have sequenced the genomes of the samples, then the platform can help you link them.
- Inter-operability & linked data
- TypeScript
- JavaScript
- HTML
- + 3
matchms
Python library for fuzzy comparison of mass spectrum data and other Python objects
- Big data
- Optimized data handling
- Python
- TeX
- Batchfile
- + 1
splithalfr
Estimates split-half reliabilities for scoring algorithms of cognitive tasks and questionnaires.
- Data Analysis
- Statistics
- R
MAGMa
MAGMa is an online application for the automatic chemical annotation of mass spectrometry data.
- Big data
- Visualization
- Python
- JavaScript
- Makefile
- + 5
GrainLearning
Unsure about the parameters of your grains in a computer simulation? Use Iterative Bayesian Filtering to learn parameter distributions from limited data. Is your model running slowly? Speed up your simulations with machine-learning surrogates. All these features are integrated within GrainLearning.
- Bayesian Inference
- Data assimilation
- Machine learning
- + 2
- Jupyter Notebook
- Python
- PureBasic
- + 1
TraP: The LOFAR Transients Pipeline
The LOFAR Transients Pipeline (or "TraP") is a Python and SQL based system for detecting and responding to transient and variable sources in a stream of astronomical images.
- Image processing
- radio astronomy
- Source association
- + 3
- Python
- PLpgSQL
- Mako
- + 1
DeepRank
Deep learning framework for data mining protein-protein interactions using CNN
- Big data
- Machine learning
- Optimized data handling
- Python
- R
- C
- + 2
Matlab codes for Probabilistic Field Approach for Motorway Driving Risk Assessment
Matlab codes for Probabilistic Field Approach for Motorway Driving Risk Assessment
- automated driving
- Collision probability
- Reachability analysis
- + 1
R package for WALRUS (Wageningen Lowland Runoff Simulator)
R package for WALRUS (Wageningen Lowland Runoff Simulator)
- discharge simulation
- hydrological model
- hydrology
- + 4