Benchmark: Create array vs Int32Array

Tests:

Int32Array
const buffer = new ArrayBuffer(512); const view = new DataView(buffer); for (let i = 0; i < 1000; i++) { const a = new Int32Array(buffer, 0, 4); }
Array
const buffer = new ArrayBuffer(512); const view = new DataView(buffer); for (let i = 0; i < 1000; i++) { const a = [] for (let j = 0; j < 4; j++) { a.push(view.getInt32(j * 4, true)); } }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Int32Array
Array

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 14 days ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/134.0.0.0 Safari/537.36

Browser/OS: Chrome 134 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
Int32Array	58263.6 Ops/sec
Array	97982.6 Ops/sec

Autogenerated LLM Summary (model llama3.2:3b, generated 6 months ago):

LLMs can make mistakes. Check important info.

I'll break down the provided benchmark JSON and explain what's being tested, compared, and its pros and cons.

**Benchmark Overview**

The test compares the allocation performance of two JavaScript arrays: an `Int32Array` (a typed array) and a regular JavaScript array. The goal is to determine which one is faster for creating an array with a specific size and layout.

**Comparison Options**

1. **Regular JavaScript Array (`[]`)**:
	* Pros:
		+ Easier to work with and more intuitive than typed arrays.
		+ No need to worry about buffer management or data type conversion.
	* Cons:
		+ Slower for large, fixed-size allocations due to the overhead of dynamic array growth.
2. **Typed Array (`Int32Array`)**:
	* Pros:
		+ Faster for large, fixed-size allocations because it uses a pre-allocated buffer.
		+ Can improve performance when working with numerical data types.
	* Cons:
		+ More complex to work with and less intuitive than regular JavaScript arrays.
		+ Requires additional setup (buffer allocation) before use.

**Library/Functionality**

The test uses the `DataView` API, which is a binary view of an ArrayBuffer in memory. It allows for reading/writing data from/to the buffer without actually copying it to/from a typed array.

In both benchmark definitions, the script creates a new ArrayBuffer with a size of 512 bytes and then allocates a new Int32Array or regular JavaScript Array on top of that buffer using the `DataView`. The allocation process is repeated 1000 times for each test case.

**Special JS Feature/Syntax**

There's no specific special JavaScript feature or syntax being used in these benchmark definitions. However, it's worth noting that the use of `true` as a parameter in the `getInt32()` method (e.g., `view.getInt32(j * 4, true)` ) is an older way to handle endianness (byte order) for 32-bit integers on some platforms.

**Other Alternatives**

If you wanted to modify this benchmark or create new ones, here are alternative approaches:

1. Compare the performance of other JavaScript array types, such as `Uint8Array`, `Float64Array`, or `BigIntArray`.
2. Test the impact of different allocation sizes (e.g., 256 bytes, 1024 bytes) on the performance difference between typed arrays and regular arrays.
3. Investigate the effect of using a specific JavaScript engine or browser version on the performance comparison.
4. Add additional workload to the test cases, such as inserting random data into the allocated arrays.

Keep in mind that the goal of this benchmark is to compare the allocation performance of two specific array types under controlled conditions. You can modify it to suit your interests and goals while maintaining consistency with the original implementation.

Related benchmarks:

Create array vs Int32Array (version: 3)

Testing allocation performance

Comparing performance of: Int32Array vs Array

Created: 2 years ago by: Registered User

Jump to the latest result

Int32Array

Array

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 6 months ago):