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Accelerating multi-channel filtering of audio signal on ARM processors

机译:在ARM处理器上加速音频信号的多通道过滤

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Tablets and smart phones are nowadays equipped with low-power processor architectures such as the ARMv7 and the ARMv8 series. These processors integrate powerful SIMD units to exploit the intrinsic data-parallelism of most media and signal processing applications. In audio signal processing, there exist multiple problems that require filtering operations such as equalizations or signal synthesizers, among others. Most of these applications can be efficiently executed today on mobile devices by leveraging the processor SIMD unit. In this paper, we target the implementation of multi-channel filtering of audio signals on ARM architectures. To this end, we consider two common audio filter structures: FIR and IIR. The latter is analyzed in two different forms: direct form I and parallel form. Our results show that the SIMD-accelerated implementation increases the processing speed by a factor of 4 with respect to the original code, and our hand-tuned SIMD implementation outperforms the auto-vectorized code by a factor of 2. These results allow us to deal in real time with multi-channel systems composed of 260 FIR filters with 256 coefficients, or 125 IIR filters with 256 coefficients, of INT16 data type.
机译:如今,平板电脑和智能手机配备了低功耗处理器体系结构,例如ARMv7和ARMv8系列。这些处理器集成了功能强大的SIMD单元,可利用大多数媒体和信号处理应用程序固有的数据并行性。在音频信号处理中,存在多个问题,这些问题尤其需要诸如均衡或信号合成器之类的滤波操作。现在,利用处理器SIMD单元,可以在移动设备上有效地执行这些应用程序中的大多数。在本文中,我们的目标是在ARM体系结构上实现音频信号的多通道过滤。为此,我们考虑两种常见的音频滤波器结构:FIR和IIR。后者以两种不同的形式进行分析:直接形式I和并行形式。我们的结果表明,相对于原始代码,SIMD加速实现将处理速度提高了4倍,而我们手动调整的SIMD实现比自动矢量化代码的性能提高了2倍。这些结果使我们能够处理实时处理多通道系统,该系统由INT16数据类型的260个256系数的FIR滤波器或125个256系数的IIR滤波器组成。

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