Multichannel active noise control (ANC) systems are commonly based on adaptive signal processing algo- rithms that require high computational capacity, which constraints their practical implementation. Graphics Processing Units (GPUs) are well known for their potential for highly parallel data processing. Therefore, GPUs seem to be a suitable platform for multichannel scenarios. However, e cient use of parallel computa- tion in the adaptive filtering context is not straightforward due to the feedback loops. This paper presents a GPU implementation of a multichannel feedforward local ANC system based on the modified filtered-x LMS algorithm working over a real-time prototype. Details regarding the parallelization of the algorithm are given. Experimental results are presented to validate the real-time performance of the multichannel ANC GPU implementation.
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