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中文摘要：
基于热路径的动态优化技术是动态二进制翻译器中提高软件运行效率的一种有效方法。如何利用基本块中已有的有限历史运行信息来识别热路径并提高它的预测命中率,同时保持计算开销没有增加是研究的重点。已有的热路径识别算法中基于模型进行预测的方法非常少,算法实现比较复杂。基于隐马尔可夫模型提出一种改进的热路径预测算法。由于状态转移序列惟一,该算法实现简单,可以提高热路径的命中率,在一定程度上改善动态二进制翻译器的性能。最后通过实验对所提出算法的有效性进行验证。
英文摘要：
Method of hot paths-based dynamic optimization is effective for improving the operational efficiency of the software in dynamic binary translator.This study focused on how to identify the hot paths by using the existing limited amount of previous operational information of basic blocks,and to enhance the hit rate of the prediction,with no increase of computational cost at the same time.There had been few methods based on models among exsiting hot paths prediction algorithms,which need complicated implementation.This paper proposed an improved hot paths prediction algorithm based on hidden Markov model.Since the sequence of state transition was unique,this algorithm was easy to implement,and could improve the hit rate of hot paths as well as the performance of the dynamic binary translator.The experimental results verified the efficiency of our algorithm.
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