Benchmark: testpow123 - MeasureThat.net

Tests:

yours
function pow(base, power) { if (power === 0) { return 1; } if (power % 2 === 0) { const multiplier = pow(base, power / 2); return multiplier * multiplier; } const multiplier = pow(base, Math.floor(power / 2)); return multiplier * multiplier * base; } var a = pow(2,20)
my
function pow2(x, y) { var q = parseInt((y / 2), 10); if (y % 2 !== 0) { return (x ** q) * (x ** q) * x; } return (x ** q) * (x ** q); } var a = pow2(2,20)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
yours
my

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 5 years ago)

User agent: Mozilla/5.0 (Linux; Android 5.1.1; SM-G7102) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/73.0.3683.90 Mobile Safari/537.36

Browser/OS: Chrome Mobile 73 on Android 5.1.1

View result in a separate tab

Test name	Executions per second
yours	115701.6 Ops/sec
my	268511.2 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down the benchmark definition and test cases to understand what is being tested.

**Benchmark Definition**
The benchmark definition represents a JavaScript function that calculates the power of a given base number raised to a certain exponent using an iterative approach with exponentiation by squaring. The function takes two parameters: `base` and `power`.

There are two different implementations of this function:

1. `pow(base, power)`:
This implementation uses a recursive approach with memoization to avoid redundant calculations.

2. `pow2(x, y)`:
This implementation uses a slightly different approach, but it also has some similarities with the first one. It appears to be an attempt to optimize the previous implementation by reducing the number of multiplications required for even exponents.

**Options being compared**

The two implementations are being compared in terms of their performance. Specifically:

* `pow(base, power)`:
	+ Uses recursion and memoization.
	+ May have higher overhead due to function call and return values.
	+ Can be optimized further by reducing the number of recursive calls.
* `pow2(x, y)`:
	+ Uses a slightly different approach with less multiplications required for even exponents.
	+ May have lower overhead than the recursive implementation.
	+ However, it's not clear if this implementation is more efficient or just appears that way due to reduced multiplication count.

**Pros and cons**

* `pow(base, power)`:
	+ Pros: potentially easier to understand and implement, can be optimized using memoization.
	+ Cons: may have higher overhead due to function call and return values.
* `pow2(x, y)`:
	+ Pros: potentially faster execution time for even exponents.
	+ Cons: harder to understand and optimize due to the different implementation.

**Library**

There is no specific library mentioned in the benchmark definition or test cases. However, it's worth noting that both implementations use built-in JavaScript functions (`Math.floor` and `parseInt`) without any additional libraries.

**Special JS features or syntax**

None of the provided code uses any special JavaScript features or syntax beyond what is standard for JavaScript programming.

**Other alternatives**

There are other possible ways to implement exponentiation by squaring, such as:

* Using bit manipulation (e.g., shifting and masking) to reduce the number of multiplications required.
* Implementing a hybrid approach that combines both recursive and iterative methods.
* Using parallel processing or multi-threading to take advantage of multiple CPU cores.

It's worth noting that for small exponents, the difference in performance between these implementations may be negligible. However, as the exponent increases, the more efficient implementation is likely to show significant advantages.

Keep in mind that measuring performance and optimizing code can be complex tasks, and there are many factors that influence the execution time of a given function. This analysis is based on a simple interpretation of the provided code and benchmark results.

Related benchmarks:

testpow123 (version: 0)

Comparing performance of: yours vs my

Created: 5 years ago by: Guest

Jump to the latest result

yours

my

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):