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Loop Parallelism Maximization for Multimedia Data Processing in Mobile Vehicular Clouds
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DOI：10.1109/TCC.2016.2607708.png)
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Mobile vehicular cloud has become popular with the rapid development of cloud computing and mobile computing. Nested loops are usually the most critical part in multimedia and high performance Digital Signal Processing (DSP) systems which are widely used in vehicular applications and systems. In order to further explore the parallelism in nested loops, we study how to maximize the system performance with considering the energy reduction for applications on Chip Multiprocessor (CMP) architectures. We propose an algorithm Energy-Aware Loop Parallelism Maximization (EALPM) to maximize the system performance with the consideration of energy reduction for applications with multidimensional nested loops. Our experiment shows that using the EALPM algorithm significantly improves both performance and energy consumption on average in comparision to other algorithms.
Keyword:
Loop parallelization
mobile vehicular cloud
energy-aware
nested loops
multimedia data processing
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