Benchmark: map v foreach - MeasureThat.net

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]||0));
}
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 and its test cases.

**Benchmark Definition JSON**

The provided JSON represents a JavaScript microbenchmark that tests the performance of two different approaches to perform matrix-vector multiplication (axpy). The benchmark definition consists of two functions:

1. `axpy(a,x,y)`: This function takes three arrays as input: `a`, `x`, and `y`. It iterates over the elements of `x` using the `forEach()` method, and for each element, it adds the corresponding element from `a` multiplied by the element from `x` to the element at the same index in `y`.
2. `axpy2(a,x,y)`: This function takes three arrays as input: `a`, `x`, and `y`. It uses the `map()` method to create a new array with the dot product of each element in `x` multiplied by the corresponding element in `a`, and then adds this result to the elements of `y`.

**Options Compared**

The benchmark compares two approaches:

1. **forEach**: This approach uses the `forEach()` method to iterate over the elements of `x`.
2. **map**: This approach uses the `map()` method to create a new array with the dot product of each element in `x` multiplied by the corresponding element in `a`.

**Pros and Cons**

* **forEach**:
	+ Pros: It is a straightforward and easy-to-understand approach that leverages the built-in `forEach()` method.
	+ Cons: It can be slower than the `map()` approach because it involves an additional function call to the callback function.
* **map**:
	+ Pros: It is often faster than the `forEach()` approach because it avoids the overhead of a callback function and uses optimized array operations.
	+ Cons: It requires more memory allocation and copying of elements, which can be slower for large arrays.

**Library Used**

There is no explicit library mentioned in the benchmark definition. However, the use of `forEach()` and `map()` suggests that the benchmark is using native JavaScript features, which are built-in to most browsers or Node.js environments.

**Special JS Features or Syntax**

* **forEach()**: This method is a part of the ECMAScript standard and is supported by all modern browsers. It allows iterating over an array's elements without exposing their index.
* **map()**: This method is also a part of the ECMAScript standard and is supported by all modern browsers. It creates a new array with the transformed values.

**Other Alternatives**

For matrix-vector multiplication, other approaches can be used, such as:

1. **Linear Algebra Libraries**: Specialized libraries like NumJS or MathJS provide optimized implementations for linear algebra operations, including matrix-vector multiplication.
2. **Native Array Methods**: Some browsers and Node.js environments provide native methods like `at()` and `fill()` that can improve performance for certain use cases.

Keep in mind that the choice of approach depends on the specific requirements of your project, such as performance, memory usage, or code readability.

Latest run results:

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

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/74.0.3729.157 Safari/537.36

Browser/OS: Chrome 74 on Windows

View result in a separate tab

Test name	Executions per second
forEach	2153733.8 Ops/sec
map	994122.8 Ops/sec

Related benchmarks:

map v foreach (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):