Benchmark: n*n vs n**2 vs Math.pow(n, 2)

Tests:

n*n
12.345*12.345
n**2
12.345**2
Math.pow(n, 2)
Math.pow(12.345, 2)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
n*n
n**2
Math.pow(n, 2)

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 9 months ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:124.0) Gecko/20100101 Firefox/124.0

Browser/OS: Firefox 124 on Windows

View result in a separate tab

Test name	Executions per second
n*n	2192170496.0 Ops/sec
n**2	2191427584.0 Ops/sec
Math.pow(n, 2)	2186906112.0 Ops/sec

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

LLMs can make mistakes. Check important info.

Measuring the performance of different mathematical operations in JavaScript can be an interesting exercise.

The provided JSON represents a benchmark test that compares three different ways to calculate the square of a number:

1. **n*n**: Simple multiplication of two numbers.
2. **n**^**2**: Exponentiation using the power operator (`**`).
3. **Math.pow(n, 2)**: Using the built-in `Math.pow()` function.

Let's break down each option and its pros and cons:

1. **n*n**:
	* Pros: Fast, simple, and widely supported.
	* Cons: Can lead to integer overflow issues if `n` is a large number, as JavaScript uses 64-bit floating-point numbers.
2. **n**^**2**:
	* Pros: More concise and expressive than manual multiplication, eliminates integer overflow issues.
	* Cons: May not be supported in older browsers or JavaScript engines that don't support exponentiation (`**`).
3. **Math.pow(n, 2)**:
	* Pros: Widely supported across modern browsers and JavaScript engines, provides a clear and concise way to calculate squares.
	* Cons: May incur a small performance overhead compared to `n*n` or `n**^2`, due to the function call.

The test also includes a control group using `Math.pow(n, 2)`, which helps to establish a baseline for comparison.

No special JavaScript features or syntax are used in this benchmark.

If you're interested in exploring alternative approaches, here are some additional options:

* Using bitwise operations: You could use the fact that `(n << 32) % 65536` can be used to calculate `n^2` efficiently, which would eliminate the need for exponentiation or the `Math.pow()` function.
* Using SIMD instructions: Modern browsers and JavaScript engines support SIMD (Single Instruction, Multiple Data) instructions, which can significantly accelerate certain mathematical operations. However, this approach is more complex and may not be supported by all browsers or platforms.

Keep in mind that benchmarking performance-critical code can be complex and nuanced, and the best approach often depends on the specific use case and target audience.

Related benchmarks:

n*n vs n**2 vs Math.pow(n, 2) (version: 0)

Comparing performance of: n*n vs n**2 vs Math.pow(n, 2)

Created: 2 years ago by: Guest

Jump to the latest result

n*n

n**2

Math.pow(n, 2)

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):