Multimedia data, especially image and video data, have become one of the most overwhelming data types on the Internet recently. Considering the user experience and real application requirements, multimedia data always...
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Multimedia data, especially image and video data, have become one of the most overwhelming data types on the Internet recently. Considering the user experience and real application requirements, multimedia data always demand a real-time processing speed. As a result, the huge amount of such data make retrieving useful information from them not only data-intensive, but also computation-intensive, which poses significant challenges to current system and architecture designs. Unfortunately, most prior studies focus only on text based retrieval systems or traditional multimedia processing applications. As far as we know, there is no systematic study on analyzing the characteristics of multimedia retrieval applications and how they might impact system and architecture designs. In this paper, we make the first attempt to construct a multimedia retrieval benchmark suite (called MMR Bench) to evaluate the corresponding system and architecture designs. To embody diverse multimedia retrieval applications, we collect eight state-of-the-art multimedia retrieval algorithms which cover the whole retrieval stages, including feature extraction, feature matching, and spatial verification. To satisfy diverse evaluation purposes, we implement multiple versions for each algorithm, including sequential version, pthread version for multi-core evaluation and data-parallel (i.e., Map-reduce) version for data-center evaluation. Moreover, MMR Bench provides flexible interfaces through retrieval stages, as well as a tool to adjust parameters and regenerating different scales of reasonable input. With such a flexible design, the algorithms in MMR Bench may be not only suitable for individual kernel-level evaluation, but also capable to be integrated into a complete infrastructure for system-level evaluation. Based on MMR Bench, we further analyze the inherent architectural characteristics, such as input size sensitivity and workload balance, which provides some insights into system and archite
We argue that the current heterogeneous computing environment mimics a complex nonlinear system which needs to borrow the concept of time-scale separation and the delayed difference approach from statistical mechanics...
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We argue that the current heterogeneous computing environment mimics a complex nonlinear system which needs to borrow the concept of time-scale separation and the delayed difference approach from statistical mechanics and nonlinear dynamics. We show that by replacing the usual difference equations approach by a delayed difference equations approach, the sequential fraction of many scientific computing algorithms can be substantially reduced. We also provide a comprehensive theoretical analysis to establish that the error and stability of our scheme is of the same order as existing schemes for a large, well-characterized class of problems.
We show that for the lattice Boltzmann model, the existing paradigm in computer science for the choice of the data structure is suboptimal. In this paper we use the requirements of physical symmetry necessary for reco...
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We show that for the lattice Boltzmann model, the existing paradigm in computer science for the choice of the data structure is suboptimal. In this paper we use the requirements of physical symmetry necessary for recovering hydrodynamics in the lattice Boltzmann description to propose a hybrid data layout for the method. This hybrid data structure, which we call a structure of an array of structures, is shown to be optimal for the lattice Boltzmann model. Finally, the possible advantages of establishing a connection between group theoretic symmetry requirements and the construction of the data structure is discussed in the broader context of grid-based methods.
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