Haggis: turbocharge a MapReduce based spatial data warehousing system with GPU engine

  title={Haggis: turbocharge a MapReduce based spatial data warehousing system with GPU engine},
  author={A. Aji and G. Teodoro and F. Wang},
  booktitle={BigSpatial '14},
  • A. Aji, G. Teodoro, F. Wang
  • Published in BigSpatial '14 2014
  • Computer Science
  • Spatial query processing involves complex multidimensional objects and compute intensive spatial operations, and therefore requires a high performance approach to meet the rapid data analytics requirements of modern spatial applications. Recently, MapReduce based spatial query systems have become a viable solution for many data intensive query tasks, and gained widespread adoption in both academia and industry. At the same time, GPUs have been successfully utilized in many applications that… CONTINUE READING
    High performance spatial queries for spatial big data: from medical imaging to GIS
    • 19
    • PDF
    A vision for GPU-accelerated parallel computation on geo-spatial datasets
    • 19
    • PDF
    The Era of Big Spatial Data: A Survey
    • 17
    • PDF
    Efficient Parallel and Distributed Algorithms for GIS Polygonal Overlay Processing
    • 13
    Parallel Processing over Spatial-Temporal Datasets from Geo, Bio, Climate and Social Science Communities: A Research Roadmap
    • 17
    Towards GPU-Accelerated Web-GIS for Query-Driven Visual Exploration
    • 4
    • PDF
    Accelerating Cross-Matching Operation of Geospatial Datasets using a CPU-GPU Hybrid Platform
    • 3
    • Highly Influenced