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One might also posit that incoming students after the implementation of STREAMS were significantly stronger, and therefore more likely to be retained.
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The implementation of streaming algorithms, typified by highly parallel computations with little reuse of input data, has been widely explored on GPUs.
This paper describes the implementation of stream header decoder and context-adaptive variable-length decoder in conformity with the H.264/AVC standard.
Based on a detailed examination of the implementation of stream power analyses at the scale of continental mountain ranges, we demonstrate that: (1) the careful selection of a digital elevation model (DEM) projection can minimize length and area distortion when analyzing large portions of the earth (such as the Himalaya or Andes) in the two-dimensional plane of a DEM.
After laying out a formal foundation for expressing windowed queries, we investigate update patterns observed in most common window variants as well as their impact on adaptations of typical operators (like windowed join, union or aggregation), thus offering more insight towards design and implementation of stream processing mechanisms.
Results from these studies are presented along with their implications for future implementation of Streaming Detection.
Several technologies have been developed, which could be selected for implementation of stream processing functionalities.
Especially, new stream processing technologies (Spark [12], AsterixDB [13]) have been created, which could be selected for implementation of stream extraction, storage and analysis functionalities.
SAMOA allows the user to create implementations of streaming algorithms, while Mahout-Samsara can be used for batch implementations.
Modern graphics processing units (GPUs) are an implementation of parallel stream processors.
Empirical assessments using a real application show that the proposed abstraction layer eases the implementation of filter-stream applications without compromising the overall application performance.
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