Benchmark: Initialize 2d array

Tests:

Functional
const arr1 = new Array(100).fill().map(()=>new Array(100).fill().map(()=>100));
New array
const arr3 = new Array(100); for (let i=0;i<100;i++) { arr3[i] = new Array(100); for (let j=0;j<100;j++) { arr3[i][j] = 100; } }
Uint8 array
const arr4 = new Uint8Array(100); for (let i=0;i<100;i++) { arr4[i] = new Array(100); for (let j=0;j<100;j++) { arr4[i][j] = 100; } }
Push destructured row
const arr5 = []; for (let i=0;i<100;i++) { const row = []; for (let j=0;j<100;j++) { row.push(100); } arr5.push([...row]); }
Push row (closure)
const arr6 = []; for (let i=0;i<100;i++) { const row = []; for (let j=0;j<100;j++) { row.push(100); } arr6.push(row); }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Functional
New array
Uint8 array
Push destructured row
Push row (closure)

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: one year ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/110.0.0.0 Safari/537.36

Browser/OS: Chrome 110 on Windows

View result in a separate tab

Test name	Executions per second
Functional	26676.0 Ops/sec
New array	38425.1 Ops/sec
Uint8 array	683.2 Ops/sec
Push destructured row	45076.6 Ops/sec
Push row (closure)	53618.3 Ops/sec

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

LLMs can make mistakes. Check important info.

Measuring the performance of JavaScript benchmarks is crucial to understand the efficiency of different approaches in various scenarios.

**Benchmark Definition JSON**

The provided benchmark definition json represents a 2D array initialization task, which is used as the basis for comparing different methods of creating and populating a 2D array.

**Test Cases**

There are four test cases that compare different approaches to create and populate a 2D array:

1. **Functional**: Uses `Array.prototype.map()` twice to create a 2D array.
	* Pros: Concise, easy to understand.
	* Cons: May be less efficient due to repeated map operations.
2. **New Array**: Creates an outer array using `new Array(100)` and then populates it with inner arrays using a nested loop.
	* Pros: More explicit control over the data structure.
	* Cons: Requires more code and may be slower due to the overhead of creating arrays.
3. **Uint8Array**: Uses `Uint8Array` instead of regular arrays to create a 2D array.
	* Pros: May be faster due to the optimized performance of Uint8Array.
	* Cons: Does not provide any additional functionality beyond regular arrays.
4. **Push Destructured Row** and **Push Row (Closure)**: Uses array literals with push() method to populate a 2D array.
	* Pros: More concise and easier to read than the New Array approach.
	* Cons: May be less efficient due to the overhead of creating array literals.

**Other Considerations**

* Using libraries like Lodash can significantly impact performance, as it adds extra overhead. In this case, no library is used.
* The use of ES6 features like `const`, `let`, and arrow functions does not appear to have a significant impact on performance in this benchmark.
* Browser-specific optimizations may also play a role in the results.

**Latest Benchmark Results**

The provided latest benchmark results show that:

* **Push Destructured Row** is the fastest approach, followed closely by **Uint8Array**, suggesting that using `new Array()` with Uint8Array can be an efficient way to create a 2D array.
* **New Array** and **Functional** are slower due to the overhead of creating arrays and repeated map operations.

Overall, this benchmark highlights the importance of considering performance optimization when writing JavaScript code.

Related benchmarks:

Initialize 2d array (version: 0)

Comparing performance of: Functional vs New array vs Uint8 array vs Push destructured row vs Push row (closure)

Created: one year ago by: Guest

Jump to the latest result

Functional

New array

Uint8 array

Push destructured row

Push row (closure)

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):