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The Smith-Waterman algorithm, which produces the optimal local alignment between pairwise sequences, is universally used as a key component in bioinformatics fields. It is more sensitive than heuristic approaches, but also more time-consuming. To speed up the algorithm, Single-Instruction Multiple-Data (SIMD) instructions have been used to parallelize the algorithm by leveraging data parallel strategy...
Job scheduling is a necessary prerequisite for performance optimization and resource management in the cloud computing system. Focusing on accurate scaled cloud computing environment and efficient job scheduling under Virtual Machine (VM) resource and Server Level Agreement (SLA) constraints, we introduce the architecture of cloud computing platform and optimization job scheduling scheme in this study...
Reinforcement learning is an area of machine learning inspired by behaviorist psychology, concerned with how software agents ought to take actions in an environment so as to maximize some notion of cumulative reward. Recently reinforcement learning has been given abroad attention, but when it is applied to solve problems with large-scale discrete or contiguous state space environments, the results...
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