ABSTRACT
Parallel computing has been around for more than 20 years. Yet geography and GIScience have not employed this technology widely or to its full potential. One reason for this may be due to a perceived lack of access to parallel computing resources in social science departments despite the fact that dual-core and multicore processors, and hyper-threading technology generating virtual cores, have been standard equipment for a number of years. However, this may change in the near future with improved accessibility to technologies such as graphics processing units (GPUs). This chapter provides an overview of parallel computing including a presentation of different types of parallel processing followed by a brief history of the field. The chapter then attempts to set out when parallel computing should be used and how, ending with an example of the use of general-purpose GPU for the development of geodemographic classifications. In an era of government initiatives on open data, the rise of big spatial data and pressing global geographical challenges to solve, greater adoption of parallel computing technologies could deliver numerous gains.
