CUDA Nifty Gridder

Documentation Status

CUDA Nifty Gridder is a GPU-accelerated implementation of Nifty Gridder.

Requirements

The system used for development must have an CUDA capable GPU and Python 3 and pip installed, along with the Python packages numpy and setuptools.

To run the unit tests Nifty Gridder must also be installed.

Installation

From the root directory of the CUDA Nifty Gridder git repo, run:

$ pip3 install --user .

Alternatively, assuming git is installed, this can also be done with:

$ pip3 install 'git+https://gitlab.com/ska-telescope/sdp/ska-gridder-nifty-cuda.git'

This is also an easy way to install the reference Nifty Gridder in order to run the unit tests.

$ pip3 install 'git+https://gitlab.mpcdf.mpg.de/ift/nifty_gridder.git'

Usage

CUDA Nifty Gridder can then be used in your Python code as:

import cuda_nifty_gridder as cng 

See the files test_ms2dirty.py and test_dirty2ms.py in tests/unit/ for more ideas on how to use CUDA Nifty Gridder.

The full documentation is available at ReadTheDocs and the GitLab Page

Unit Tests

If PyTest is installed, the unit tests can be run from the root directory of the repo as:

$ py.test -s

the -s provides feedback during the tests, and can be omitted.

Otherwise the tests can be run as:

$ python3 test.py