Benchmark: Compare GCD - MeasureThat.net

Script Preparation code:

function gcd(a, b){
  var divisor = 2, 
      greatestDivisor = 1;

  if (a < 2 || b < 2)
     return 1;
  
  while(a >= divisor && b >= divisor){
   if(a %divisor == 0 && b% divisor ==0){
      greatestDivisor = divisor;      
    }
   divisor++;
  }
  return greatestDivisor;
}

function gcd1(a,b){
    var divisor = a < b ? a : b;  	
    
    if(a < 2 || b < 2){
        return 1;
    }
    
    while(divisor > 0){
        if(a % divisor === 0 && b % divisor === 0){
            return divisor;
        }
        divisor--;
    }
}

function gcd2(a, b){
    var x;
    
    while(b !== 0){
        x = a % b;
        a = b;
        b = x;
    }
    
    return a;
}

function gcd3(a, b){
    if(b === 0)
        return a;
    return gcd3(b, a % b);
}

Tests:

Original
gcd(1012, 10580);
Improvement
gcd1(1012, 10580);
Recursion
gcd3(1012, 10580);
Reverse Engineered Recursion
gcd2(1012, 10580);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Original
Improvement
Recursion
Reverse Engineered Recursion

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 26 days ago):

LLMs can make mistakes. Check important info.

I'll provide an explanation of the provided benchmark, its options, pros and cons, and other considerations.

**Benchmark Definition**

The provided JSON represents a benchmark for comparing three different implementations of the Greatest Common Divisor (GCD) algorithm. The GCD is a mathematical function that returns the largest number that divides two given numbers without leaving a remainder.

**Options Compared**

There are four options compared in this benchmark:

1. **Original**: This implementation uses a simple iterative approach to calculate the GCD.
2. **Improvement**: This implementation improves upon the original by using a more efficient algorithm with fewer iterations.
3. **Recursion**: This implementation uses recursive function calls to calculate the GCD, which can be less efficient than iterative approaches due to the overhead of function calls and returns.
4. **Reverse Engineered Recursion**: This implementation is an optimized version of the recursive approach, using a loop to mimic the behavior of the recursive function.

**Pros and Cons**

Here are some pros and cons of each option:

1. **Original**:
	* Pros: Simple to understand and implement, easy to debug.
	* Cons: May be slower than other implementations due to more iterations.
2. **Improvement**:
	* Pros: More efficient than the original implementation, reducing the number of iterations.
	* Cons: May be harder to understand for beginners due to the use of a different algorithm.
3. **Recursion**:
	* Pros: Can be easier to implement and understand for some people, as it follows a more natural mathematical approach.
	* Cons: More expensive in terms of CPU cycles due to function calls and returns.
4. **Reverse Engineered Recursion**:
	* Pros: Optimized for performance, reducing the overhead of recursive function calls.
	* Cons: May be harder to understand for those not familiar with reverse engineering.

**Library Usage**

There is no explicit library usage in this benchmark definition or test cases. However, it's worth noting that JavaScript engines often rely on built-in functions and optimizations to execute benchmarks, which may affect the results.

**Special JS Feature/Syntax**

None of the special JS features or syntax are used in these benchmark definitions or test cases.

**Other Considerations**

When running this benchmark, it's essential to consider the following factors:

* **Browser and OS differences**: The benchmark results are specific to Chrome 84 on Windows 7. Running the benchmark on different browsers or operating systems may yield different results.
* **Optimization techniques**: Some optimizations, like compiler-specific tricks or hardware-dependent features, might affect the benchmark results.
* **Cache and memory effects**: The cache and memory behavior can significantly impact the performance of these algorithms, especially in a single-threaded environment.

**Alternative Approaches**

If you'd like to explore alternative approaches for calculating the GCD, consider the following:

* **Fibonacci-based algorithm**: This method uses Fibonacci numbers to calculate the GCD.
* **Binary exponentiation**: This approach uses binary exponentiation to efficiently compute the greatest common divisor of two large numbers.

Keep in mind that these alternatives may have different performance characteristics and might be more suitable for specific use cases.

Latest run results:

Run details: (Test run date: 4 years ago)

User agent: Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/84.0.4147.105 Safari/537.36

Browser/OS: Chrome 84 on Windows 7

View result in a separate tab

Test name	Executions per second
Original	142899.0 Ops/sec
Improvement	136172.9 Ops/sec
Recursion	843324.7 Ops/sec
Reverse Engineered Recursion	4119273.5 Ops/sec

Related benchmarks:

Compare GCD (version: 0)

Compare GCD

Comparing performance of: Original vs Improvement vs Recursion vs Reverse Engineered Recursion

Created: 8 years ago by: Guest

Jump to the latest result

Original

Improvement

Recursion

Reverse Engineered Recursion

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 26 days ago):