Towards a Scalable In Situ Fast Fourier Transform
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866915131873558528 |
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| author | Kulkarni, Sudhanshu Loring, Burlen Bethel, E. Wes |
| author_facet | Kulkarni, Sudhanshu Loring, Burlen Bethel, E. Wes |
| contents | The Fast Fourier Transform (FFT) is a numerical operation that transforms a function into a form comprised of its constituent frequencies and is an integral part of scientific computation and data analysis. The objective of our work is to enable use of the FFT as part of a scientific in situ processing chain to facilitate the analysis of data in the spectral regime. We describe the implementation of an FFT endpoint for the transformation of multi-dimensional data within the SENSEI infrastructure. Our results show its use on a sample problem in the context of a multi-stage in situ processing workflow. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_01843 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Towards a Scalable In Situ Fast Fourier Transform Kulkarni, Sudhanshu Loring, Burlen Bethel, E. Wes Distributed, Parallel, and Cluster Computing The Fast Fourier Transform (FFT) is a numerical operation that transforms a function into a form comprised of its constituent frequencies and is an integral part of scientific computation and data analysis. The objective of our work is to enable use of the FFT as part of a scientific in situ processing chain to facilitate the analysis of data in the spectral regime. We describe the implementation of an FFT endpoint for the transformation of multi-dimensional data within the SENSEI infrastructure. Our results show its use on a sample problem in the context of a multi-stage in situ processing workflow. |
| title | Towards a Scalable In Situ Fast Fourier Transform |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2402.01843 |