Benchmark: x ** 0.5 vs Math.sqrt(x)

Script Preparation code:

var numbers = Array.from(Array(10000), (_,x) => (Math.random()*x));

Tests:

Math.sqrt
numbers.forEach(x => Math.sqrt(x));
sqrt with Math.pow
numbers.forEach(x => x ** 0.5);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Math.sqrt
sqrt with Math.pow

Fastest: N/A

Slowest: N/A

Autogenerated LLM Sumamry (model llama3.2:3b, generated 3 days ago):

LLMs can make mistakes. Check important info.

I'll break down the provided benchmark test cases and explain what's being tested, compared, and their pros and cons.

**Benchmark Definition**

The first part of the benchmark definition json represents a single JavaScript microbenchmark:
```json
{
    "Name": "x ** 0.5 vs Math.sqrt(x)",
    "Description": null,
    "Script Preparation Code": "var numbers = Array.from(Array(10000), (_,x) => (Math.random()*x));",
    "Html Preparation Code": null
}
```
Here, we have:

* `Name`: a descriptive title for the benchmark.
* `Description`: an empty string, which means there's no detailed explanation of the benchmark's purpose.
* `Script Preparation Code`: this code is executed before running the actual benchmark. It generates an array of 10,000 random numbers between 0 and 1 (exclusive) using the `Math.random()` function and the spread operator (`...`). The resulting array will be used to test various mathematical operations on these values.
* `Html Preparation Code`: an empty string, indicating that no HTML-specific code is needed for this benchmark.

**Individual Test Cases**

The next part of the benchmark definition represents individual test cases:
```json
[
    {
        "Benchmark Definition": "numbers.forEach(x => Math.sqrt(x));",
        "Test Name": "Math.sqrt"
    },
    {
        "Benchmark Definition": "numbers.forEach(x => x ** 0.5);",
        "Test Name": "sqrt with Math.pow"
    }
]
```
Here, we have two test cases:

* The first test case (`"numbers.forEach(x => Math.sqrt(x));"`): it uses the built-in `Math.sqrt()` function to calculate the square root of each number in the `numbers` array.
* The second test case (`"numbers.forEach(x => x ** 0.5);"`): it uses a non-standard syntax, `x ** 0.5`, which is equivalent to calculating the square root of `x`. Note that this syntax is specific to some JavaScript engines.

**Pros and Cons**

Now, let's discuss the pros and cons of each approach:

* **Math.sqrt()**: This is the recommended way to calculate the square root in modern JavaScript. It's a built-in function, widely supported by most browsers and Node.js versions.
	+ Pros: efficient, reliable, well-documented, and widely supported.
	+ Cons: may be slower than alternative methods (more on this later).
* **x ** 0.5**: This non-standard syntax is specific to some JavaScript engines, such as V8 (used by Google Chrome) and SpiderMonkey (used by Mozilla Firefox).
	+ Pros: potentially faster than `Math.sqrt()` due to compiler optimizations.
	+ Cons: not supported by all browsers or Node.js versions, which may lead to compatibility issues.

**Library Usage**

In this benchmark, the `Array.from()` function is used to create an array of random numbers. This is a modern JavaScript feature introduced in ECMAScript 2015 (ES6). It's a built-in function that creates a new array from an iterable object, which can be useful for initializing arrays or other data structures.

**Special JS Features/Syntax**

There are no special JavaScript features or syntax used in this benchmark. The tests only rely on the standard JavaScript functions and operators.

**Other Alternatives**

If you're interested in exploring alternative methods for calculating square roots, here are a few options:

* **Bisection method**: an iterative algorithm that uses repeated division by two to estimate the square root.
* **Newton's method**: an optimization technique that uses an initial guess and iteratively improves it using the derivative of the function being optimized.
* **Binary search**: an algorithm that can be used to find the square root by searching for the closest integer.

Keep in mind that these alternative methods might not be as efficient or reliable as `Math.sqrt()` and may require more computational resources.

Latest run results:

Run details: (Test run date: 4 months ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:126.0) Gecko/20100101 Firefox/126.0

Browser/OS: Firefox 126 on Windows

View result in a separate tab

Test name	Executions per second
Math.sqrt	16895.1 Ops/sec
sqrt with Math.pow	32537.6 Ops/sec

Related benchmarks:

x ** 0.5 vs Math.sqrt(x) (version: 0)

Comparing performance of: Math.sqrt vs sqrt with Math.pow

Created: 4 months ago by: Guest

Jump to the latest result

Math.sqrt

sqrt with Math.pow

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Sumamry (model llama3.2:3b, generated 3 days ago):