High-performance computing (HPC) involves using multiple interconnected computers combined with parallel processing approaches to solve problems that are too large or complex for a single computer. Generally, HPC systems, such as supercomputers and clusters, use high-bandwidth, low-latency network interconnects to enable fast and efficient communication across processes running on the HPC system. In geographic information science (GIScience), growth in data size and analytical complexity drive more demand for computing power and the need for HPC. Researchers and practitioners use HPC to process more geospatial data, run finer-grained simulations, and explore problems at spatial and temporal scales that were previously impossible. The key challenge in using HPC is coordinating and synchronizing dozens, hundreds, or thousands of processors simultaneously.
Where should a retail business occur or locate within a region? What would that trade area look like? Should a retail expansion occur and how would that affect sales of other nearby existing locations? Would a new retail location have the right demographic or socio-economic customer base to be profitable? These are important questions for retailers to consider. Within the evolving landscape of GIS, there is more geospatial data than ever before about the potential customer. In retail, the application of maps and mapping technology is growing to include commercial real estate, logistics, and marketing to name a few. There has been an increased momentum across commercial applications for geospatial technologies delivered in an easy to comprehend format for a variety of end users.