During 20th century few branches of science have proved themselves to be more industrially applicable than Plasma science and processing. Across a vast range of discharge types and regimes, and through industries spanning semiconductor manufacture, surface sterilisation, food packaging and medicinal treatment, industry continues to find new usefulness in this physical phenomenon well into 21st century. To better cater to this diverse motley of industries there is a need for more detailed and accurate understanding of plasma chemistry and kinetics, which drive the plasma processes central to manufacturing. Extensive efforts have been made to characterise plasma discharges numerically and mathematically leading to the development a number of different approaches. In our work we concentrate on the Particle-In-Cell (PIC) - Monte Carlo Collision (MCC) approach to plasma modelling. This method has for a long time been considered computationally prohibitive by its long run times and high computational resource expense. However, with modern advances in computing, particularly in the form of relatively cheap accelerator devices such as GPUs and co-processors, we have developed a massively parallel simulation in 1 and 2 dimensions to take advantage of this large increase in computing power. Furthermore, we have implemented some changes to the traditional PIC-MCC implementation to provide a more generalised simulation, with greater scalability and smooth transition between low and high (atmospheric) pressure discharge regimes. We also present some preliminary physical and computational benchmarks for our PIC-MCC implementation providing a strong case for validation of our results.