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Survival of the synthesis—GPU accelerating evolutionary sound matching

Renney, Harri; Gaster, Benedict; Mitchell, Thomas J.

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Authors

Harri Renney

Benedict Gaster Benedict.Gaster@uwe.ac.uk
Associate Professor in Physical Computing

Tom Mitchell Tom.Mitchell@uwe.ac.uk
Professor of Audio and Music Interaction



Abstract

Manually configuring synthesizer parameters to reproduce a particular sound is a complex and challenging task. Researchers have previously used different optimization algorithms, including evolutionary algorithms to find optimal sound matching solutions. However, a major drawback to these algorithms is that they typically require large amounts of computational resources, making them slow to execute. This article proposes an optimized design for matching sounds generated by frequency modulation (FM) audio synthesis using the graphics processing unit (GPU). A benchmarking suite is presented for profiling the performance of three implementations: serial CPU, data-parallel CPU, and data-parallel GPU. Results have been collected and discussed from a high-end NVIDIA desktop and a mid-range AMD laptop. Using the default configuration for simple FM, the GPU accelerated design had a speedup of 128 (Formula presented.) over the naive serial implementation and 8.88 (Formula presented.) over the parallel CPU version on a desktop with an Intel i7 9800X CPU and NVIDIA RTX GeForce 2080Ti GPU. Furthermore, the relative speedup over the naive serial implementation continues to increase beyond simple FM to more advanced structures. Further observations include comparisons between integrated and discrete GPUs, toggling optimizations, and scaling evolutionary strategy population size.

Journal Article Type Article
Acceptance Date Dec 14, 2021
Online Publication Date Jan 4, 2022
Publication Date May 1, 2022
Deposit Date Jan 12, 2022
Publicly Available Date Jan 5, 2023
Journal Concurrency and Computation: Practice and Experience
Print ISSN 1532-0626
Electronic ISSN 1532-0634
Publisher Wiley
Peer Reviewed Peer Reviewed
Volume 34
Issue 10
Article Number e6824
DOI https://doi.org/10.1002/cpe.6824
Public URL https://uwe-repository.worktribe.com/output/8542871

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Copyright Statement
This is the peer reviewed version of the following article: Renney, H., Gaster, B., & Mitchell, T. J. (2022). Survival of the synthesis—GPU accelerating evolutionary sound matching. Concurrency and Computation: Practice and Experience, 34(10), which has been published in final form at https://doi.org/10.1002/cpe.6824. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited.





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