A Novel SIMD-Optimized Implementation for Fast and Memory-Efficient Trigonometric Computation
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arXiv
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| Auteurs principaux: | , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866912233484713984 |
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| author | Goyal, Nikhil Dev Arora, Parth |
| author_facet | Goyal, Nikhil Dev Arora, Parth |
| contents | This paper proposes a novel set of trigonometric implementations which are 5x faster than the inbuilt C++ functions. The proposed implementation is also highly memory efficient requiring no precomputations of any kind. Benchmark comparisons are done versus inbuilt functions and an optimized taylor implementation. Further, device usage estimates are also obtained, showing significant hardware usage reduction compared to inbuilt functions. This improvement could be particularly useful for low-end FPGAs or other resource-constrained devices. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_10831 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Novel SIMD-Optimized Implementation for Fast and Memory-Efficient Trigonometric Computation Goyal, Nikhil Dev Arora, Parth Mathematical Software This paper proposes a novel set of trigonometric implementations which are 5x faster than the inbuilt C++ functions. The proposed implementation is also highly memory efficient requiring no precomputations of any kind. Benchmark comparisons are done versus inbuilt functions and an optimized taylor implementation. Further, device usage estimates are also obtained, showing significant hardware usage reduction compared to inbuilt functions. This improvement could be particularly useful for low-end FPGAs or other resource-constrained devices. |
| title | A Novel SIMD-Optimized Implementation for Fast and Memory-Efficient Trigonometric Computation |
| topic | Mathematical Software |
| url | https://arxiv.org/abs/2502.10831 |