Abstract

Physics-based sound synthesis usually requires high computational costs and this results in a restriction of its use in real-time applications. This motivates us to implement the sound synthesis algorithm of plucked-string instruments using multi-core processor architectures and determine the optimal processing element (PE) configuration for the target instruments. To determine the optimal PE configuration, we evaluate the impacts of a sample-per-processing element (SPE) ratio that is defined as the amount of sample data directly mapped to each PE on system performance and both area and energy efficiencies using architectural and workload simulations. For the acoustic guitar, the highest area and energy efficiencies are achieved at a SPE ratio of 5,513 and 2,756, respectively, for the synthesis of musical sounds sampled at 44.1 kHz. In the case of the classical guitar, the maximum area and energy efficiencies are achieved at a SPE ratio of 22,050 and 5,513, respectively. In addition, the synthetic sounds were very similar to original sounds in their spectra. Furthermore, we conducted MUSHRA subjective listening test with ten subjects including nine graduate students and one professor from the University of Ulsan, and the evaluation of the synthetic sounds was excellent.

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