Benchmark: Distance Calc, pow vs mult

Script Preparation code:

var point1 = {x:5,y:10};
var point2 = {x:20,y:15};

Tests:

MULT
Math.sqrt((point1.x-point2.x)*(point1.x-point2.x)+(point1.y-point2.y)*(point1.y-point2.y));
POW
Math.sqrt(Math.pow(point1.x-point2.x,2)+Math.pow(point1.y-point2.y,2));

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
MULT
POW

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/110.0.0.0 Safari/537.36

Browser/OS: Chrome 110 on Windows

View result in a separate tab

Test name	Executions per second
MULT	3253879.0 Ops/sec
POW	3271987.0 Ops/sec

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

LLMs can make mistakes. Check important info.

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

**Benchmark Overview**

The benchmark is designed to compare the performance of two approaches for calculating the Euclidean distance between two points in 2D space: `Math.pow` (multiplied) vs. multiplication (e.g., `(a-b)*(c-d)`). The benchmark uses two test cases:

1. `POW`: Calculates the distance using `Math.sqrt(Math.pow(point1.x-point2.x,2)+Math.pow(point1.y-point2.y,2))`.
2. `MULT`: Calculates the distance directly using `(point1.x-point2.x)*(point1.y-point2.y)`.

**Options Compared**

The benchmark compares two options:

* `POW` (Using `Math.pow` for multiplication): This approach uses the exponentiation operator (`**`) to calculate the squared differences between corresponding coordinates, and then takes the square root of the sum. This can be seen as a more straightforward way to compute the distance using arithmetic operations.
* `MULT`: This approach calculates the difference in each coordinate separately, multiplies them together, and then computes the square root of the product.

**Pros and Cons**

Pros:

* **POW**: This approach is likely faster because it uses the optimized exponentiation algorithm in JavaScript's `Math.pow` function. Additionally, this method can be seen as more intuitive for computing distances using a direct multiplication formula.
* **MULT**: This approach can be faster when working with large numbers or when a different mathematical structure is used to compute the distance.

Cons:

* **POW**:
	+ May have overhead due to the square root calculation.
	+ May not be as efficient for very large numbers due to the exponentiation operation.
* **MULT**:
	+ Requires careful handling of edge cases, such as division by zero or negative values.
	+ Can lead to overflow issues when working with large numbers.

**Library and Special JS Features**

Neither test case uses any libraries. However, it's worth noting that JavaScript's `Math.sqrt` function is a built-in library call.

There are no special JavaScript features used in these benchmark tests.

**Alternative Approaches**

Other approaches for calculating the Euclidean distance could include:

* Using a library like NumJS or mathjs, which provide optimized implementations of mathematical functions.
* Implementing the distance calculation using SIMD instructions (if available on the target platform).
* Using a different algorithm, such as the Manhattan distance or the Minkowski distance.

In terms of optimization techniques, other approaches might include:

* Minimizing branching by avoiding conditional statements in the benchmark code.
* Reducing function call overhead through inlining or caching results.
* Leveraging hardware acceleration (e.g., GPU acceleration) for compute-intensive tasks.

Related benchmarks:

Distance Calc, pow vs mult (version: 0)

Comparing performance of: MULT vs POW

Created: 6 years ago by: Guest

Jump to the latest result

MULT

POW

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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