Parallel map analysis on 2-D grids

In landscape ecology, computer modeling is used to assess habitat fragmentation and its ecological iMPLications. Specifically, maps (2-D grids) of habitat clusters must be analyzed to determine number, sizes and geometry of clusters. Models prior to this study relied upon sequential Fortran-77 programs which limited the sizes of maps and densities of clusters which could be analyzed. In this paper, we present more efficient computer models which can exploit recursion or parallelism. Significant improvements over the original Fortran-77 programs have been achieved using both recursive and nonrecursive C implementations on a variety of workstations such as the Sun Sparc 2, IBM RS/6000-350, and HP 9000-750. Parallel implementations on a 4096-processor MasPar MP-1 and a 32-processor CM-5 are also studied. Preliminary experiments suggest that speed improvements for the parallel model on the MasPar MP-1 (written in MPL) and on the CM-5 (written in C using CMMD) can be as much as 39 and 34 times faster, respectively, than the most efficient sequential C program on a Sun Sparc 2 for a 512 map. An important goal in this research effort is to produce a scalable map analysis algorithm for the identification and characterization of clusters for relatively large maps on massively-parallelmore » computers.« less