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This project is a fork of the original GPU De-dedispersion library (https://github.com/ajameson/dedisp/), intended to be used/modified for the FDD project.

Image Domain Gridding (IDG) is a fast method for convolutional resampling (gridding/degridding) of radio astronomical data (visibilities). Direction-dependent effects (DDEs) or A-tems can be applied in the gridding process.

This is a fork of https://github.com/benvanwerkhoven/energy_experiments, where only the kernel tuner scripts for some selected radio astronomy kernels have been maintained. The rest of the history is pruned.

A fork of https://git.astron.nl/lofar2.0/cobalt, with only the Beamformer kernel code and tests. Refactored to make the code 'stand-alone' as much as possible, while still being somewhat compatible with the original code. Since the original repository is over 500 Mb, all large files have been pruned from the history.

DP3: streaming processing pipeline for radio interferometric data

Complex CUDA GEMM Library provides complex GEMM kernels for complex data.

EdgeDP3: to bring DP3 on the edge. Experimental DP3 verion to new features and optimizations.

DP3: streaming processing pipeline for radio interferometric data