  A radio interferometer indirectly measures the intensity distribution of the
sky over the celestial sphere. Since measurements are made over an irregularly
sampled Fourier plane, synthesising an intensity image from interferometric
measurements requires substantial processing. Furthermore there are distortions
that have to be corrected. In this thesis, a new high-performance image
synthesis tool (imaging tool) for radio interferometry is developed.
Implemented in C++ and CUDA, the imaging tool achieves unprecedented
performance by means of Graphics Processing Units (GPUs). The imaging tool is
divided into several components, and the back-end handling numerical
calculations is generalised in a new framework. A new feature termed
compression arbitrarily increases the performance of an already highly
efficient GPU-based implementation of the w-projection algorithm. Compression
takes advantage of the behaviour of oversampled convolution functions and the
baseline trajectories. A CPU-based component prepares data for the GPU which is
multi-threaded to ensure maximum use of modern multi-core CPUs. Best
performance can only be achieved if all hardware components in a system do work
in parallel. The imaging tool is designed such that disk I/O and work on CPU
and GPUs is done concurrently. Test cases show that the imaging tool performs
nearly 100$\times$ faster than another general CPU-based imaging tool.
Unfortunately, the tool is limited in use since deconvolution and A-projection
are not yet supported. It is also limited by GPU memory. Future work will
implement deconvolution and A-projection, whilst finding ways of overcoming the
memory limitation.
