Benchmark: distance - MeasureThat.net

Script Preparation code:

var ax = 100;
var ay = 200;

var bx = 400;
var by = 600;

Tests:

hyp
Math.hypot(bx - ax, by - ay);
sqrt
var a = bx - ax; var b = by - ay; var c = Math.sqrt(a * a + b * b);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
hyp
sqrt

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 2 months ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36 Edg/133.0.0.0

Browser/OS: Chrome 133 on Windows

View result in a separate tab

Test name	Executions per second
hyp	111784360.0 Ops/sec
sqrt	219840464.0 Ops/sec

Autogenerated LLM Summary (model llama3.2:3b, generated 6 months ago):

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark and explain what's being tested.

**Benchmark Definition**

The benchmark is defined in JSON format, which includes:

* `Script Preparation Code`: This code is executed once before running each test case. It sets up variables for the benchmark:
	+ `ax` and `ay` are initialized with values 100 and 200 respectively.
	+ `bx` and `by` are initialized with values 400 and 600 respectively.
* `Html Preparation Code`: This field is empty, which means no HTML code is prepared before running each test case.

**Individual Test Cases**

There are two test cases:

1. **hyp**: The benchmark definition is a single line of JavaScript code that calculates the distance between two points using the `Math.hypot` function:
```javascript
Math.hypot(bx - ax, by - ay);
```
This function returns the Euclidean distance between the points `(ax, ay)` and `(bx, by)`.

2. **sqrt**: The benchmark definition is a multi-line code snippet that calculates the same distance using a different approach:
```javascript
var a = bx - ax;
var b = by - ay;

var c = Math.sqrt(a * a + b * b);
```
This code first calculates the differences in x and y coordinates (`a` and `b`) and then uses the Pythagorean theorem to calculate the distance (`c`).

**Options Compared**

The two test cases compare the performance of using the `Math.hypot` function versus calculating the square root and summing the squares manually.

**Pros and Cons**

* **Using Math.hypot**:
	+ Pros: This method is more concise and likely to be faster due to its optimized implementation in the JavaScript engine.
	+ Cons: It may not be as intuitive or easy to understand for developers who are not familiar with this function.
* **Calculating square root manually**:
	+ Pros: This approach can be more educational, as it teaches developers about the underlying mathematics of calculating distances.
	+ Cons: It is likely to be slower and less efficient due to the overhead of calculating the square root and summing the squares.

**Library**

There is no specific library used in this benchmark. However, `Math.hypot` is a built-in JavaScript function that uses optimized implementations provided by the browser's JavaScript engine.

**Special JS Feature or Syntax**

None are mentioned in this benchmark.

**Other Alternatives**

If you wanted to benchmark alternative methods for calculating distances, some possible options could include:

* Using the Haversine formula (for calculating great-circle distances between two points on a sphere)
* Implementing a custom distance algorithm using bitwise operations or other low-level techniques
* Comparing the performance of different libraries like Three.js or Babylon.js for 3D graphics rendering

Keep in mind that benchmarking such alternative methods would likely require significant modifications to the benchmark code and might not be as relevant to most use cases.

Related benchmarks:

distance (version: 0)

Comparing performance of: hyp vs sqrt

Created: 7 years ago by: Guest

Jump to the latest result

hyp

sqrt

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 6 months ago):