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Update README.md
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Geolm authored Jan 29, 2024
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Expand Up @@ -132,12 +132,36 @@ If you use the macro \_\_MATH_INTRINSINCS_FAST\_\_ some functions will have less
## is it fast?
The goal of this library is to provide math function with a good precision with every computation done in AVX/NEON. Performance is not the focus.

Here's the benchmark results on my old Intel Core i7 from 2018 (time for 32 billions of computed values)
* mm256_sin_ps : 29887ms
* mm256_acos_ps : 24650ms
* mm256_exp_ps : 24387ms
Here's the benchmark results on my old Intel Core i7 from 2018 for 10 billions of operations

### precision mode

* mm256_acos_ps: 7795.786 ms
* mm256_asin_ps: 7034.068 ms
* mm256_atan_ps: 7797.666 ms
* mm256_cbrt_ps: 15130.169 ms
* mm256_cos_ps: 8600.893 ms
* mm256_sin_ps: 8288.432 ms
* mm256_exp_ps: 8647.793 ms
* mm256_exp2_ps: 10130.995 ms
* mm256_log_ps: 10423.453 ms
* mm256_log2_ps: 5232.928 ms

### fast mode

Using \_\_MATH_INTRINSINCS_FAST\_\_

* mm256_acos_ps: 4823.037 ms
* mm256_asin_ps: 4982.991 ms
* mm256_atan_ps: 7213.156 ms
* mm256_cbrt_ps: 14716.824 ms
* mm256_cos_ps: 5441.888 ms
* mm256_sin_ps: 5186.748 ms
* mm256_exp_ps: 8429.838 ms
* mm256_exp2_ps: 5262.944 ms
* mm256_log_ps: 10318.204 ms
* mm256_log2_ps: 5130.680 ms

Use \_\_MATH_INTRINSINCS_FAST\_\_ if needed.

## why AVX2 ?

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