The Essence of High-Performance Computing in Zimbabwe’s National Spatial Data Infrastructure Analysis

Abstract

The study looked at the essence of high-performance computing in national spatial data analysis, towards inclusive national development in Zimbabwe. This qualitative research explored the perceptions of the increasing availability of national spatial data, looking at the challenges being faced in the handling and analysis of this big data, hence the growing need for more sophisticated tools and techniques to analyse this data efficiently and accurately. Spatial data has become ubiquitous, for example, Global Positioning System data, with increasingly sheer sizes in recent years. The applications of big spatial data span a wide spectrum of interests including tracking infectious disease, climate change simulation, and natural disaster detection, among others. High-performance computing (HPC) has emerged as a critical tool in addressing this need of efficiently collecting, managing, storing, and analysing geospatial data streams as well as handling the "Vs" (volume, variety, velocity, veracity, and value) of big data, since the massive datasets must be analysed in the context of space and time. This dissertation, therefore, explores the role of High-Performance Computing in national spatial data analysis, examining its benefits and challenges for this purpose. Drawing on a review of the literature, case studies, questionnaires, and semi-structured interviews with experts in the field, the dissertation presents an overview of High-Performance Computing architecture and software, as well as a framework for evaluating its efficacy in national spatial data analysis. The main findings from the research suggest that HPC can significantly improve the speed and accuracy of national spatial data processing, enabling users to better analyse large and complex datasets. However, there are some challenges such as cost, data management, and the need for specialized skills and expertise that were taken note of and needed to be addressed. The inquiries about these points appearing, concerns and challenges of the appropriation of High-Performance Computing innovation in spatial data analysis, were taken off from a case study about Zimbabwe National Geospatial and Space Agency (ZINGSA) in utilizing the graphic explanatory strategy. Eighteen surveys were recalled out of the twenty surveys that were conveyed and analysed. The investigate suggested that ZINGSA can embrace High-Performance Computing innovation in its operations, on the off chance that it is curiously on the side of ICT human assets through training, scientific missions, and advancements. In expansion, curiously on the side of security through putting the non-critical application and information within the cloud, or through making hybrid HPC which comprises of cloud-based HPC for non-basic applications like email and physical HPC data iv centre for basic and touchy applications and information. Without a question, the best administration has a crucial part in the appropriation of this innovation in its operations even through its decisions and facilities. Overall, this dissertation highlights the importance of High-Performance Computing in Zimbabwe’s national spatial data analysis and offers practical recommendations for its effective use.