As a web developer working on data visualization and scientific computing projects, I've often found JavaScript's native math capabilities lacking. The hunt for robust standard library led me to stdlib-js.
The promise of stdlib
The stdlib project caught my eye with its impressive set of features:
- Comprehensive mathematical functions
- Focus on numerical precision
- Cross-platform consistency
- Extended functionality beyond native Math
Benchmarking Reality
I ran benchmarks comparing stdlib against native JavaScript Math operations across 100,000 rows of data. The results were suprising:
Performance Comparison Table
Operation | Performance Difference | Precision (Max Diff) | Precision (Avg Diff) | Notes |
---|---|---|---|---|
exp | 189.44% slower | 0.000e+0 | 0.000e+0 | Largest performance gap |
log10 | 58.94% slower | 4.441e-16 | 1.142e-17 | Significant slowdown |
ln/log | 33.63% slower | 0.000e+0 | 0.000e+0 | Notable performance impact |
tan | 31.87% slower | 0.000e+0 | 0.000e+0 | Slower trig operation |
acos | 29.17% slower | 4.441e-16 | 4.569e-17 | Slower inverse trig |
sin | 24.54% slower | 1.110e-16 | 3.101e-18 | Basic trig affected |
cos | 23.00% slower | 1.110e-16 | 3.039e-18 | Basic trig affected |
asin | 22.74% slower | 2.220e-16 | 1.219e-17 | Inverse trig impact |
atan2 | 17.02% slower | 2.220e-16 | 6.958e-18 | Moderate slowdown |
atan | 13.86% slower | 1.110e-16 | 2.675e-18 | Better performing inverse trig |
ceil | 2.84% slower | 0.000e+0 | 0.000e+0 | Minimal impact |
abs | 1.99% slower | 0.000e+0 | 0.000e+0 | Negligible difference |
floor | 2.22% faster | 0.000e+0 | 0.000e+0 | Slight improvement |
round | 1.44% faster | 0.000e+0 | 0.000e+0 | Minor gain |
sqrt | 2.68% faster | 0.000e+0 | 0.000e+0 | Better performance |
hypot | 1.18% faster | 0.000e+0 | 0.000e+0 | Slight improvement |
The Good
Basic operations showed modest improvements:
- sqrt: 6.23% faster
- round: 3.02% faster
- floor: 2.02% faster
The Not So Good
Complex operations took a significant hit:
- exp: 189.85% slower
- log10: 59.37% slower
- trig functions: 25-33% slower
Precision Trade-off
The precision differences were minimal, with a maximum difference of 4.441e-16. Most operations whoed identical results between stdlib-js and native Math.
When to Use stdlib-js
- Basic mathematical operations
- Projects requiring guaranteed cross-platform behavior
- Cases where consistent results matter more than raw speed
Looking Forward
There's potential for improvement - converting stdlib-js to WebAssembly could boost performance by running close to native speed, particularly for those complex operations currently showing significant slowdown. But until that happens, the choice between stdlin-js and native Math requires careful consideration of your specific needs.
Bottom Line
stdlib-js is a solid library taht delviers on its promise of consistency and extended functionality. However, the performance trade-offs mean it's not always the best choice. For my projects, I'll be using native approach and maybe in the future will try to compile stdlib-js to WASM to test if its really faster.
Have you tried stdlib in your projects? I'd be curious to hear about your experiences with mathematical computations in JavaScript.
Resources
- Run live demo here
- Benchmark repo
- Asadbek Karimov
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