Modern Accelerator Technologies for Geographic Information Science

Modern Accelerator Technologies for GIScience.- Introduction to GPGPU.- Intel® Xeon Phi(TM) Coprocessors.- Accelerating Geocomputation with Cloud Computing.- Parallel Primitives based Spatial Join of Geospatial Data on GPGPUs.- Utilizing CUDA-enabled GPUs to support 5D scientific geovisualization: a case study of simulating dust storm events.- A Parallel Algorithm to Solve Near-Shortest Path Problems on Raster Graphs.- CUDA-Accelerated HD-ODETLAP: Lossy High Dimensional Gridded Data Compression.- Accelerating Agent-Based Modeling Using Graphics Processing Units.- Large-Scale Pulse Compression for Costas Signal with GPGPU.- Parallelizing ISODATA Algorithm for Unsupervised Image Classification on GPU.- Accelerating Mean Shift Segmentation Algorithm on Hybrid CPU/GPU Platforms.- Simulation and analysis of cluster-based caching replacement based on temporal and spatial locality of tile access.- A High-Concurrency Web Map Tile Service Built with Open-Source Software.- Improved Parallel Optimal Choropleth Map Classification.- Pursuing Spatiotemporally Integrated Social Science using Cyberinfrastructure.- Opportunities and Challenges for Urban Land-use Change Modeling using High-performance Computing.- Modern Accelerator Technologies for Spatially-explicit Integrated Environmental Modeling.