Abstract
A classical technique to vectorize code that contains control flow is a control-flow to data-flow conversion. In that approach statements are augmented with masks that denote whether a given vector lane participates in the statement’s execution or idles. If the scheduling of work to vector lanes is performed statically, then some of the vector lanes will run idle in case of control flow divergences or varying work intensities across the loop iterations. With an increasing number of vector lanes, the likelihood of divergences or heavily unbalanced work assignments increases and static scheduling leads to a poor resource utilization. In this paper, we investigate different approaches to dynamic SIMD vector lane scheduling using the Mandelbrot set algorithm as a test case. To overcome the limitations of static scheduling, idle vector lanes are assigned work items dynamically, thereby minimizing per-lane idle cycles. Our evaluation on the Knights Corner and Knights Landing platform shows, that our approaches can lead to considerable performance gains over a static work assignment. By using the AVX-512 vector compress and expand instruction, we are able to further improve the scheduling.
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Acknowledgements
This work has been funded by SAXonPHI – Intel Parallel Computing Center Dresden at the Center for Information Services and High Performance Computing, TU Dresden, by the Research Center for Many-core HPC (IPCC) at Zuse Institute Berlin, and by the Intel Parallel Computing Center at RWTH Aachen University.
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Krzikalla, O., Wende, F., Höhnerbach, M. (2016). Dynamic SIMD Vector Lane Scheduling. In: Taufer, M., Mohr, B., Kunkel, J. (eds) High Performance Computing. ISC High Performance 2016. Lecture Notes in Computer Science(), vol 9945. Springer, Cham. https://doi.org/10.1007/978-3-319-46079-6_25
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DOI: https://doi.org/10.1007/978-3-319-46079-6_25
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