KEYWORDS: Data processing, Parallel processing, Parallel computing, Raster graphics, Radon, Data centers, Video processing, Image processing, Video, Data modeling
In this paper, we investigate the problem of enabling block level parallelism, for multi-dimensional data sets, with
arbitrary but static causal dependency between blocks that constitute the data set. As the use of video and other multi-dimensional
data sets becomes more common place and the algorithms used to process them become more complex,
there is greater need for effective parallelization schemes. We describe a method for synchronizing the execution of
multiple processors to respect the dependency structure and calculate the total processing time as a function of the
number of parallel processors. We also provide an algorithm to calculate the optimal starting times for each processor
which enables them to continuously process blocks without the need for synchronizing with other processors, under the
assumption that the time to process each block is fixed.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.