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

Script Preparation code:

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

Tests:

x*x
numbers.forEach(x => x*x);
sqrt with Math.pow
numbers.forEach(x => Math.pow(x,2));

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

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

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 3 months ago)

User agent: Mozilla/5.0 (X11; Linux x86_64; rv:146.0) Gecko/20100101 Firefox/146.0

Browser/OS: Firefox 146 on Linux

View result in a separate tab

Test name	Executions per second
x*x	9415.4 Ops/sec
sqrt with Math.pow	6248.5 Ops/sec

Autogenerated LLM Summary (model gpt-4o-mini, generated one year ago):

LLMs can make mistakes. Check important info.

The benchmark provided compares two different methods of squaring numbers in JavaScript: using the multiplication operator (`x * x`) and the `Math.pow` function (`Math.pow(x, 2)`).

### Comparison of Approaches

1. **Multiplication (`x * x`)**:
    - **Test Case**: `numbers.forEach(x => x * x);`
    - **Execution Speed**: This approach achieved approximately 385,589 executions per second in the benchmark results.
    - **Pros**:
        - Generally faster than using `Math.pow`, as observed in the benchmark results. Direct multiplication is typically optimized by JavaScript engines, making it a more efficient choice.
        - Simplified syntax, easier to read and understand, especially for a simple operation like squaring.
    - **Cons**:
        - Limited to squaring (or multiplying) operations; cannot be as flexible as `Math.pow` for other powers that might require more complex calculations.

2. **Power Function (`Math.pow`)**:
    - **Test Case**: `numbers.forEach(x => Math.pow(x, 2));`
    - **Execution Speed**: This method showed a significantly lower performance with about 36,559 executions per second.
    - **Pros**:
        - More versatile, as it can handle any exponent (e.g., `Math.pow(x, n)` allows for any power, not just squares).
        - Potentially clearer in intent when dealing with non-integer or higher exponents, especially when the operation is not strictly squared.
    - **Cons**:
        - Slower performance compared to simple multiplication, as seen in the benchmark results.
        - Overhead from function calls and additional processing, which can lead to less efficient execution in tight loops, like the one used in the benchmark.

### Considerations
When choosing between these two approaches for performance-sensitive applications, the specific use case matters. If you are strictly squaring numbers, the `x * x` approach is generally recommended due to its better performance. However, if your code needs to handle more general power calculations, `Math.pow` is necessary, although it may sacrifice some speed in doing so.

### Other Alternatives
For squaring numbers, there are few alternatives that may be considered:
- **Exponentiation Operator (`**`)**: In modern JavaScript, you can use the exponentiation operator (e.g., `x ** 2`). This also provides an efficient way to square numbers and has similar performance characteristics to `x * x` in many cases.
- **Bitwise Operations**: While not applicable for squaring in a general sense, certain mathematical operations can leverage bitwise operators for performance gains, although these would typically not simplify squaring.

### Conclusion
In conclusion, for the specific case of squaring numbers in JavaScript, the multiplication operator (`x * x`) is generally the superior choice in terms of performance, while `Math.pow` offers broader functionality for other mathematical needs. Software engineers should always consider the context in which they are operating and weigh the importance of performance against code clarity and intent when selecting mathematical operations in their applications.

Related benchmarks:

Math.pow(x,2) vs x*x (version: 1)

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

Created: one year ago by: Guest

Jump to the latest result

x*x

sqrt with Math.pow

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model gpt-4o-mini, generated one year ago):