Fire ignition and weather prediction maps in Virtual Fire are produced daily. However, the processing time needed for this creation was considerably high, due to large input datasets. To confront this problem, the creation of the maps has been based on a HPC pilot application running on Microsoft Windows HPC server. HPC provides the computing power that is required for the fire ignition and weather map calculations because of the large geographical extent and the high spatiotemporal resolution. A computation cluster is used, composed of two quad-core processing nodes (one head node and one computing node). The map resolution for both sequential and parallel execution was the same, i.e. 500 m. For the fire ignition probability maps the “task flow” model was used where a set of unlike tasks are run in a prescribed order, usually because one task depends on the result of another task. Whenever, two or more tasks can run independently then they are assigned to a separate core and run concurrently. By following the HPC approach, the computation speed was increased of about 33%, by activating up to five cores simultaneously. More specifically, processing mean time of sequential processing was initially 333 s, while HPC decreased the time to 224 s. Even if these durations are considered relatively small, the benefit of HPC would emerge for higher resolutions and greater geographic areas, where the processing times would be much higher.