Benchmark: map v foreach fair

Script Preparation code:

function axpy(a,x,y){ 
   y.forEach((_,i)=>y[i]+=a*x[i]);
}
function axpy2(a,x,y){ 
   return x.map((xi,i)=>xi*a+y[i]);
}
a = Math.random()*2-1;
x = (new Array(100)).fill(0).map((x,i)=>Math.random()*2-1);
y = (new Array(100)).fill(0).map((x,i)=>Math.random()*2-1);

Tests:

forEach
axpy(a,x,y)
map
y=axpy2(a,x,y)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
forEach
map

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 29 days ago):

LLMs can make mistakes. Check important info.

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

**Benchmark Definition:**

The benchmark consists of two script preparation codes:

1. `axpy(a,x,y)`: This function is designed to perform an element-wise vector multiplication between arrays `x` and `y`, and store the result in array `y`. The function iterates over each element in the array using a traditional for loop.
2. `y=axpy2(a,x,y)`: This function uses the `map()` method to achieve the same result as `axpy()`. It takes an array `x` and returns a new array with the elements multiplied by `a`, then adds the corresponding element from array `y`.

**Comparison:**

The two functions are compared in terms of performance. The test case "forEach" uses `axpy()` and is expected to be slower, while "map" uses `axpy2()`, which is optimized for performance.

**Pros and Cons:**

1. **`axpy()` (forEach)**:
	* Pros:
		+ Easy to understand and implement.
		+ Can be more predictable for developers familiar with traditional loops.
	* Cons:
		+ May be slower due to the overhead of explicit loop control.
2. **`axpy2()` (map)**:
	* Pros:
		+ Optimized for performance using `map()`, which is a built-in array method.
		+ Can provide better parallelization and caching benefits on modern hardware.
	* Cons:
		+ May be less intuitive for developers without experience with `map()` or functional programming concepts.

**Library:**

There are no explicit libraries mentioned in the benchmark definition, but `Array.prototype.forEach` is used in `axpy()`. This method is a built-in part of the JavaScript language and does not require any additional libraries to function.

**Special JS feature/syntax:**

The use of `map()` in `axpy2()` demonstrates the "map" function, which is a built-in array method in JavaScript. This syntax allows developers to perform operations on each element of an array without explicit loops.

**Other alternatives:**

To achieve the same result as `axpy()`, alternative implementations could include:

1. Using `Array.prototype.reduce()` instead of `forEach`.
2. Implementing a custom loop using `for...of` or `for...in` loops.
3. Utilizing other array methods like `every()`, `some()`, or `filter()`.

However, these alternatives would likely be less performant and more verbose than the built-in `map()` method used in `axpy2()`.

Latest run results:

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

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/98.0.4758.102 Safari/537.36

Browser/OS: Chrome 98 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
forEach	3225629.2 Ops/sec
map	1653249.9 Ops/sec

Related benchmarks:

map v foreach fair (version: 0)

Comparing performance of: forEach vs map

Created: 5 years ago by: Guest

Jump to the latest result

forEach

map

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 29 days ago):