Benchmark: Math.pow(x,0.5) vs Math.sqrt(x) (inverse order)

Script Preparation code:

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

Tests:

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

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

Latest run results:

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

User agent: Mozilla/5.0 (X11; Linux x86_64; rv:134.0) Gecko/20100101 Firefox/134.0

Browser/OS: Firefox 134 on Linux

View result in a separate tab

Test name	Executions per second
Math.sqrt	15122.8 Ops/sec
sqrt with Math.pow	16690.3 Ops/sec

Autogenerated LLM Summary (model gpt-4o-mini, generated 3 months ago):

LLMs can make mistakes. Check important info.

The benchmark described in the provided JSON compares the performance of two approaches for computing the square root of numbers: using the `Math.pow` function and using the `Math.sqrt` function.

### Options Compared
The two test cases are:
1. **Math.pow(x, 0.5)**: This approach uses the `Math.pow` function to compute the square root by raising the number `x` to the 0.5 power.
2. **Math.sqrt(x)**: This approach uses the specialized `Math.sqrt` function, which is explicitly designed to calculate the square root of a number.

### Pros and Cons
#### Math.pow(x, 0.5)
- **Pros**:
  - The `Math.pow` function is a more generalized function that can handle any exponent, not just square roots. This makes it versatile for other mathematical calculations that involve exponents.
- **Cons**:
  - It is typically slower for calculating square roots compared to `Math.sqrt`, as `Math.pow` has additional overhead for determining the power.
  - An exponent of 0.5 can lead to potential floating-point precision issues, especially in the context of large or small numbers.

#### Math.sqrt(x)
- **Pros**:
  - The `Math.sqrt` function is specialized for square root calculations, which helps it perform better and faster than `Math.pow` for this specific case.
  - It is simpler and clearer in intent, making code easier to read and maintain.
- **Cons**:
  - It is limited to calculating square roots only, making it less versatile than `Math.pow`.

### Benchmark Results
From the benchmark results provided, we can see the executions per second for each approach:
- **sqrt with Math.pow**: 16,690.27 executions per second
- **Math.sqrt**: 15,122.76 executions per second

Interestingly, the benchmark indicates that using `Math.pow(x, 0.5)` performed better in this particular test, which might be attributed to factors such as engine optimizations in the JavaScript runtime (e.g., V8 in Chrome or SpiderMonkey in Firefox).

### Other Considerations
It's crucial to keep in mind that performance may vary depending on multiple factors, including the JavaScript engine implementation, the current state of optimization in the browser, and the specific hardware on which the benchmark is executed.

### Alternatives
Other options for calculating square roots in JavaScript could include:
- **Using a custom square root implementation**: This might involve implementing an algorithm such as the Newton-Raphson method, which can optimize for specific use cases or precision requirements.
- **Using third-party libraries**: Libraries like `math.js` provide additional mathematical functions and can handle complex calculations involving square roots and other operations, though they might introduce overhead compared to built-in functions.

In summary, this benchmark illustrates the efficiency of different methods for calculating square roots and emphasizes the importance of understanding the pros and cons of each approach, particularly in performance-sensitive applications.

Related benchmarks:

Math.pow(x,0.5) vs Math.sqrt(x) (inverse order) (version: 1)

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

Created: 3 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 Summary (model gpt-4o-mini, generated 3 months ago):