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Project Summary
Although locating and
navigation devices embedded in smartphones
have already generated large volumes of
location and trajectory data, the next
generation of consumer electronics are likely
to generate even larger volumes of
location-dependent data where spatial and
trajectory data management techniques will
play critical roles in understanding the data
to facilitate decision making. Modern
Graphics Processing Units (GPUs) are capable
of general computing. Current generation of
commodity GPUs have large numbers of
processing cores, support even larger numbers
of current threads and provide high memory
bandwidth, yet are available at affordable
prices. The massively data parallel computing
power of GPUs makes the hardware ideal for
spatial and trajectory data management which
is both data and computing intensive.
This project develops
parallel indexing structures and query
processing algorithms for spatial and
trajectory data on GPUs to provide high
performance which is crucial in speeding up
existing applications and enabling new
scientific and business inquiries. The
project achieves its goals by developing: 1)
novel spatial indexing techniques on GPUs; 2)
novel spatial joins on GPUs; 3) novel
trajectory segmentation and indexing
techniques and trajectory similarity query
processing techniques on GPUs; and 4) an
end-to-end prototype system incorporated with
open source database and GIS systems for
performance evaluations and real world
applications. Compared with existing spatial
and trajectory data management systems that
are mostly disk-resident and adopt a serial
CPU computing model, the performance of GPU
accelerated main-memory based systems is
expected to achieve several orders of
magnitude speedup and brings the performance
of spatial and trajectory queries to a new
level.
The research results are
beneficial to many applications, such as
transportation, urban planning, wild bird
ecology, and epidemiology of infectious
diseases. Collaboration is carried out with
transportation engineers at the University
Transportation Research Center in New York
City and ecology scientists at the University
of Oklahoma’s Earth Observing and
Modelling Facility. The project also makes
important impacts on education as it provides
training for students in the areas of national
critical needs: database research, high
performance computing, GPU programming, GIS,
transportation, mobile and ecology
applications.
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