Benchmark: mathjs random vs Math.random

HTML Preparation code:

<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjs/10.0.0/math.js" integrity="sha512-+lwWRCGAWhCLRPruF7ruYxRlMQuRD1H9C/Pc/HYcuxachoLufBO7OU66bfFnVsFaHQj3S/CunEimw8alVvkl+Q==" crossorigin="anonymous" referrerpolicy="no-referrer"></script>

Tests:

mathjs
math.random()
vanilla
Math.random()

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
mathjs
vanilla

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: one year ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/136.0.0.0 Safari/537.36

Browser/OS: Chrome 136 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
mathjs	37201252.0 Ops/sec
vanilla	142097904.0 Ops/sec

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):

LLMs can make mistakes. Check important info.

Let's dive into the world of JavaScript microbenchmarks!

**Overview**

The provided JSON represents a benchmark test created on MeasureThat.net, where users can compare the performance of different JavaScript libraries and built-in functions. The goal is to measure how well each approach performs mathematical operations.

**What is tested?**

Two specific benchmarks are compared:

1. `math.random()`: This tests the `random()` function from Math.js, a library that provides an alternative implementation of mathematical functions.
2. `Math.random()`: This tests the built-in `random()` function from JavaScript's built-in `Math` object.

**Options being compared**

The main options being compared are:

* **Library**: Math.js (the external library) vs. JavaScript's built-in `Math` object (vanilla).
* **Implementation**: The specific implementation of `random()` in each option: Math.js uses a non-deterministic algorithm, while the vanilla `Math.random()` function uses a pseudo-random number generator.

**Pros and Cons**

Here are some pros and cons for each approach:

**Library (Math.js)**

Pros:

* Can provide better performance for certain mathematical operations.
* Allows for more control over the implementation and potential optimizations.

Cons:

* Requires an external library, which may add overhead to the test.
* May require additional setup and configuration.

**Vanilla (JavaScript's built-in `Math` object)**

Pros:

* Built-in, no additional overhead or dependencies required.
* Easy to use and integrate with other code.

Cons:

* May not provide optimal performance for all mathematical operations.
* Implementation details may be less controllable compared to an external library.

**Special JS feature: ES6 modules**

In the benchmark definition JSON, there is a reference to the `integrity` attribute in the script tag. This indicates that the Math.js library uses ES6 module syntax (`import` and `export`) instead of traditional CommonJS module syntax (`.require()`). MeasureThat.net may be using this feature to ensure that the benchmarking results are accurate.

**Other alternatives**

Some alternative approaches could include:

* Using a different JavaScript engine or interpreter, such as SpiderMonkey (used by Mozilla's Firefox browser) or V8 (used by Google Chrome).
* Implementing custom mathematical functions in JavaScript.
* Comparing performance with other programming languages or libraries that provide similar functionality.

Keep in mind that MeasureThat.net may use these alternative approaches in future benchmark tests, providing users with more options to compare and contrast different coding techniques.

Related benchmarks:

mathjs random vs Math.random (version: 0)

Comparing performance of: mathjs vs vanilla

Created: 4 years ago by: Guest

Jump to the latest result

mathjs

vanilla

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):