Benchmark: math pow vs multiply (with few extra variants, but without multiplication example)

Script Preparation code:

function powNaive(x, y) {
	if (!y) return 1;
	let tmp = x;
	for (let i = 1; i < y; i++) {
		tmp *= x;
  	}
	return tmp;
}

// from https://codereview.stackexchange.com/a/217369
function pow2B(x, y) {
    if (y < 2) { return y ? x : 1 }
    if (y & 1) { return x * pow2B(x, y & 0x7FFFFFFE)}
    const p = pow2B(x, y >> 1);
    return p * p;
}

// other two functions from the same stackexchange post
function pow(x, y) {
  if (!y) { return 1 }
  let tmp = res = x;
  for (let i = 1; i < y; i++) {
    for (let j = 1; j < x; j++) { tmp += res }
    res = tmp;
  }
  return res;
}

function pow2(x, y) {
  if (!y) { return 1; }
  if (y % 2) {
    return x * pow2(x, y - 1);
  }
  const p = pow2(x, y/2);
  return p * p;
}

Tests:

Math.pow
var x = Math.pow(54,2);
pow2 bitwise
var y = pow2B(54, 2)
pow2 summ
var y = pow(54, 2)
pow2 multi
var y = pow2(54, 2)
pow (mult for loop)
var y = powNaive(54, 2)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Math.pow
pow2 bitwise
pow2 summ
pow2 multi
pow (mult for loop)

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 27 days ago):

LLMs can make mistakes. Check important info.

Let's break down the benchmark and its options.

**Benchmark Definition**

The benchmark measures the performance of different methods for calculating powers of numbers, specifically `Math.pow`, four variants of `pow` (`powNaive`, `pow2B`, `pow2 summ`, and `pow2 multi`), and two more variants that use bitwise operations to reduce the number of multiplications required.

**Options Compared**

The options compared in this benchmark are:

1. **`Math.pow`**: The built-in method for calculating powers, which uses repeated multiplication.
2. **`powNaive`**: A custom implementation that uses a loop to multiply the base by itself for each exponent iteration.
3. **`pow2B`**: Another custom implementation that uses bitwise operations to reduce the number of multiplications required.
4. **`pow2 summ`**: Yet another custom implementation that uses a summing approach to calculate powers.
5. **`pow2 multi`**: A custom implementation that uses multiplication-based approach.

**Pros and Cons**

Here's a brief summary:

* **`Math.pow`**:
	+ Pros: Simple, widely supported, and efficient for small exponents.
	+ Cons: May use repeated multiplication, which can be slow for large exponents.
* **`powNaive`**:
	+ Pros: Easy to understand and implement, suitable for small exponents.
	+ Cons: Uses repeated multiplication, making it slower than `Math.pow`.
* **`pow2B`**:
	+ Pros: Efficiently reduces the number of multiplications required using bitwise operations.
	+ Cons: Requires understanding of bitwise operations and may be less readable.
* **`pow2 summ`**:
	+ Pros: Uses a summing approach, which can be efficient for large exponents.
	+ Cons: May not be as widely supported or well-understood as other methods.
* **`pow2 multi`**:
	+ Pros: Efficiently uses multiplication-based approach.
	+ Cons: Requires understanding of the implementation details.

**Libraries and Special JS Features**

There are no libraries used in this benchmark, but some custom implementations (`pow2B`, `pow2 summ`, and `pow2 multi`) use bitwise operations. No special JS features are mentioned, but some implementations may rely on understanding of bitwise operations or summing approaches.

**Alternatives**

If you're interested in exploring alternative methods for calculating powers, here are a few options:

* **Exponentiation by squaring**: A method that uses repeated squaring to calculate powers.
* **Binary exponentiation**: A method that uses binary arithmetic and exponentiation by squaring to calculate powers efficiently.
* **Horner's method**: An algorithm for evaluating polynomials using nested multiplication.

These alternatives may offer improved performance or efficiency over the methods compared in this benchmark, but their implementation can be more complex and challenging.

Latest run results:

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

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/118.0.0.0 Safari/537.36

Browser/OS: Chrome 118 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
Math.pow	15862194.0 Ops/sec
pow2 bitwise	15572650.0 Ops/sec
pow2 summ	291965.8 Ops/sec
pow2 multi	10332326.0 Ops/sec
pow (mult for loop)	32333926.0 Ops/sec

Related benchmarks:

math pow vs multiply (with few extra variants, but without multiplication example) (version: 0)

Comparing performance of: Math.pow vs pow2 bitwise vs pow2 summ vs pow2 multi vs pow (mult for loop)

Created: one year ago by: Guest

Jump to the latest result

Math.pow

pow2 bitwise

pow2 summ

pow2 multi

pow (mult for loop)

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 27 days ago):