Benchmark: Map vs For Loop - MeasureThat.net

Script Preparation code:

var a = [];
for (var i = 0; i < 1e6; i++) {
  a[i] = Math.random();
}

Tests:

Map
var b = a.map(n => n * 2);
For Loop
var b = []; for (var i = 0; i < a.length; i++) { b[i] = a[i] * 2; }
foreach
var b = a.forEach(n => n * 2);
pre-allocated for loop
var b = new Array(a.length); for (var i = 0; i < a.length; i++) { b[i] = a[i] * 2; }
pre-allocated unrolled for loop
var b = new Array(a.length); for (var i = 0; i < a.length/4; i++) { b[i*4] = a[i*4] * 2; b[i*4+1] = a[i*4+1] * 2; b[i*4+2] = a[i*4+2] * 2; b[i*4+3] = a[i*4+3] * 2; }
++for loop
var b = new Array(a.length); for (var i = 0; i < a.length; ++i) { b[i] = a[i] * 2; }
--for loop
var b = new Array(a.length); for (var i = a.length; i >= 0; --i) { b[i] = a[i] * 2; }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Map
For Loop
foreach
pre-allocated for loop
pre-allocated unrolled for loop
++for loop
--for loop

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 3 years ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10.15; rv:92.0) Gecko/20100101 Firefox/92.0

Browser/OS: Firefox 92 on Mac OS X 10.15

View result in a separate tab

Test name	Executions per second
Map	67.0 Ops/sec
For Loop	75.1 Ops/sec
foreach	160.8 Ops/sec
pre-allocated for loop	77.7 Ops/sec
pre-allocated unrolled for loop	76.7 Ops/sec
++for loop	75.4 Ops/sec
--for loop	8.3 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 provided benchmark and explain what is being tested, compared, and their pros/cons.

**Benchmark Definition**

The benchmark measures the performance of different approaches for mapping an array to create a new array with doubled values. The script preparation code initializes an empty array `a` with 1 million elements using a `for` loop. Then, the HTML preparation code is null, indicating that no additional HTML is needed.

**Test Cases**

The benchmark consists of six test cases:

1. **Map**: Uses the built-in `map()` function to create a new array `b` by doubling each value in `a`.
2. **For Loop**: Uses a traditional `for` loop to iterate over `a` and assign doubled values to `b`.
3. **foreach**: Uses the `forEach()` method to iterate over `a` and apply the doubling operation to each value.
4. **pre-allocated for loop**: Creates an array `b` with the same length as `a` and uses a traditional `for` loop to assign doubled values.
5. **pre-allocated unrolled for loop**: Similar to the previous test, but assigns four doubled values at once using bit-shifting operations.
6. **++for loop** and **--for loop**: Similar to the previous tests, but increments or decrements the loop counter instead of using traditional indexing.

**Library:**

None of the test cases rely on any external libraries beyond JavaScript's built-in functions (`map()`, `forEach()`).

**Special JS Feature/Syntax:**

The only notable feature is the use of bit-shifting operations (e.g., `b[i*4] = a[i*4] * 2;`) in the **pre-allocated unrolled for loop** test case. This allows for more efficient iteration over the array elements.

**Pros and Cons:**

Here's a brief summary of each approach:

1. **Map**: Quick and easy to implement, but may incur overhead due to the function call.
	* Pros: Easy to use, minimal code
	* Cons: May be slower due to function call overhead
2. **For Loop**: Traditional iteration, good for large datasets.
	* Pros: Fast, efficient, can handle large datasets
	* Cons: More verbose code, requires explicit indexing
3. **foreach**: Convenient and readable, but may have performance implications.
	* Pros: Easy to use, readable code
	* Cons: May be slower due to method call overhead
4. **pre-allocated for loop**: Efficient iteration with minimal memory allocation.
	* Pros: Fast, efficient, can handle large datasets
	* Cons: Requires manual indexing and array creation
5. **pre-allocated unrolled for loop**: Optimized for performance by using bit-shifting operations.
	* Pros: Very fast, optimized for performance
	* Cons: More complex code, requires understanding of bit-shifting operations

**Other Alternatives**

Some alternative approaches could include:

1. Using `Array.prototype.reduce()` to create a new array with doubled values.
2. Utilizing `Buffer` or `Typed Array` libraries for more efficient array operations.
3. Implementing a custom iterative algorithm using low-level memory management.

Keep in mind that these alternatives may have their own trade-offs and might not be suitable for all use cases.

**Benchmark Results**

The provided benchmark results show the relative performance of each approach, with the optimized **pre-allocated unrolled for loop** achieving the fastest execution time.

Related benchmarks:

Map vs For Loop (version: 0)

Comparing performance of: Map vs For Loop vs foreach vs pre-allocated for loop vs pre-allocated unrolled for loop vs ++for loop vs --for loop

Created: 8 years ago by: Guest

Jump to the latest result

Map

For Loop

foreach

pre-allocated for loop

pre-allocated unrolled for loop

++for loop

--for loop

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):