next up previous
Next: High/Medium Quality Forage Up: Deer Component Previous: Reproduction



Since the landscape is divided among the 32 processing nodes, a deer's search area may encompass more than one processor. Without knowledge of data across processor boundaries, it becomes impossible for the animal to select a new grid location similar to the one it would have chosen in the sequential model.

Similar parallel ecological models developed in the past have determined whether an animal should move to a new processor by using a decision method referred to as PMI (Preferential Moving Index) averaging. With this method, a PMI value is computed at the beginning of each simulation day, using data from all or portions of a processor's grid cells, and then broadcast to every other processor. If the animal cannot locate enough forage on its own processor, the nearest neighbor processor with the greatest PMI average above a threshold is chosen and the animal is sent to that processor to continue its foraging sequence [BU95].

Although PMI averaging may result in decreased parallel execution time for some ecological applications, this method was not used in the parallel SIMPDEL model for several reasons:

  1. The per processor area is too large and may increase in future implementations.
  2. Forage amounts decrease after each deer grazes. With simulation test populations from 2,000 to 20,000, the PMI averages would quickly become invalid, and frequent updating of the PMI averages would most likely offset any gain realized by their use.

  3. Available forage amounts in the same grid cell differ for bucks, does, and does with fawns, since these amounts are computed using the maximum water depths that each class of deer can withstand.

  4. Maintenance of PMI averages for both high and medium quality forage classes would be required.

  5. A processor's PMI average is dependent upon area, thus different partition sizes would produce different results.

Therefore it was necessary to develop a different parallel method for determining deer movement locations based on the most recent forage levels. The parallel method for the deer forage search relies on all processors containing grid locations within a deer's search area to examine the necessary grid cells in parallel.

next up previous
Next: High/Medium Quality Forage Up: Deer Component Previous: Reproduction

Michael W. Berry (
Wed Oct 11 14:53:18 EDT 1995