Wave Field Synthesis (WFS) aims to replicate true sound field in an extended listening area with the help of loudspeaker arrays. WFS practical setups are heavily computational, as they need to drive many loudspeakers to accurately render multiple virtual sources. Thus, performance bottleneck occurs due to the sequential implementation on PCs with few cores. In addition, real-time spatial audio reproduction systems like WFS are subjected to hard real- time constraints, limiting system throughput and require cascading of several PCs to improve performance. In this paper, a fast and efficient graphics processing unit (GPU) based implementation of WFS is proposed to enhance the system throughput by extracting maximum data parallelism in the algorithm. The proposed method, implemented on NVidia C2075 GPU, uses block based partitioning approach to achieve peak system throughput of 1,400 Msamples per second, while rendering up to 200 real-time sound sources.
['Rishabh Ranjan', 'Woon-Seng Gan']
Fast and efficient real-time GPU based implementation of wave field synthesis