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Qinling: A Parametric Model in Speculative Multithreading
2017
Symmetry
Speculative multithreading (SpMT) is a thread-level automatic parallelization technique that can accelerate sequential programs, especially for irregular applications that are hard to be parallelized by conventional approaches. Thread partition plays a critical role in SpMT. Conventional machine learning-based thread partition approaches applied machine learning to offline guide partition, but could not explicitly explore the law between partition and performance. In this paper, we build a
doi:10.3390/sym9090180
fatcat:hz5343sctzcydcmkmtsmg2vmru