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Improving particle filter performance using SSE instructions

机译:使用SSE指令提高颗粒过滤器的性能

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Robotics researchers are often faced with real-time constraints, and for that reason algorithmic and implementation-level optimization can dramatically increase the overall performance of a robot. In this paper we illustrate how a substantial run-time gain can be achieved by taking advantage of the extended instruction sets found in modern processors, in particular the SSE1 and SSE2 instruction sets. We present an SSE version of Monte Carlo Localization that results in an impressive 9x speedup over an optimized scalar implementation. In the process, we discuss SSE implementations of atan, atan2 and exp that achieve up to a 4x speedup in these mathematical operations alone.
机译:机器人研究人员通常面临实时约束,因此,算法和实现级别的优化可以显着提高机器人的整体性能。在本文中,我们说明了如何利用现代处理器中的扩展指令集(特别是SSE1和SSE2指令集)来获得可观的运行时增益。我们提供了蒙特卡洛本地化的SSE版本,与优化的标量实现相比,该版本可实现令人印象深刻的9倍加速。在此过程中,我们将讨论atan,atan2和exp的SSE实现,仅这些数学运算即可实现高达4倍的加速。

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