Benchmark: ext math pow vs multiply

Script Preparation code:

var DATA = [];
for (var i = 0 ; i < 100; i++) {
    DATA.push(Math.random() * i);
}

Tests:

pow
for (var i in DATA) { var x = Math.pow(DATA[i], 2); }
mult
for (var i in DATA) { var x = DATA[i] * DATA[i]; }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
pow
mult

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Linux; Android 9; SAMSUNG SM-G611MT) AppleWebKit/537.36 (KHTML, like Gecko) SamsungBrowser/17.0 Chrome/96.0.4664.104 Mobile Safari/537.36

Browser/OS: Chrome Mobile 96 on Android

View result in a separate tab

Test name	Executions per second
pow	4513.8 Ops/sec
mult	6070.4 Ops/sec

Autogenerated LLM Summary (model gemma2:9b, generated 2 months ago):

LLMs can make mistakes. Check important info.

This benchmark compares two ways to calculate the square of a number: using `Math.pow()` and multiplying the number by itself.

Here's a breakdown:

**Options Compared:**

* **`Math.pow(DATA[i], 2)`:** This uses the built-in `Math.pow()` function, which calculates the result of raising one number to the power of another. In this case, it squares the value from the `DATA` array.
* **`DATA[i] * DATA[i]`:** This directly multiplies the value from the `DATA` array by itself.

**Pros and Cons:**

* **`Math.pow()`**: 
    * **Pro:**  Potentially more efficient for a wider range of exponents (not just squares). The `Math.pow()` function is likely optimized internally.
    * **Con:**  Might be slightly slower for squaring due to the overhead of calling a separate function.

* **Direct Multiplication**: 
    * **Pro:** Simpler and more direct code. Less function call overhead.
    * **Con:** Not as versatile for calculating powers other than squares.

**Other Considerations:**

The benchmark measures *execution speed*.  The results indicate that, in this specific case, multiplying directly (`DATA[i] * DATA[i]`) is slightly faster on the tested device/browser combination.

**Alternatives:**
* **Libraries:** Libraries like Lodash or NumJS could offer optimized math functions for performance-critical applications. However, they add an external dependency and might introduce slight overhead.
* **Assembly/SIMD Instructions:** For truly maximum performance, you could explore using lower-level programming techniques like assembly language or SIMD (Single Instruction, Multiple Data) instructions to directly manipulate data at a faster rate. This is generally only necessary for highly demanding applications.

Remember that benchmark results can vary significantly depending on the hardware, software, and specific code implementation.

Related benchmarks:

ext math pow vs multiply (version: 0)

Comparing performance of: pow vs mult

Created: 3 years ago by: Guest

Jump to the latest result

pow

mult

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model gemma2:9b, generated 2 months ago):