Benchmark: OffscreenCanvas GetImageData

Script Preparation code:

let canvas = document.createElement("canvas")
let width = 3460;
let height = 2160;
canvas.width = width;
canvas.height = height;
let canvas2 = new OffscreenCanvas(width, height)
let ctx = canvas.getContext('2d')
let ctx2 = canvas2.getContext('2d')
let imageData = new ImageData(width,height);
ctx.putImageData(imageData,0, 0);
document.body.append(canvas)
ctx2.putImageData(imageData,0 ,0)
window.ctx = ctx;
window.ctx2 = ctx2
window.width = width;
window.height = height;

Tests:

Normal
ctx.getImageData(0,0, width, height) let imageData = new ImageData(1,1); ctx.putImageData(imageData,5,5);
OffscreenCanvas
ctx2.getImageData(0,0, width, height) let imageData = new ImageData(1,1); ctx2.putImageData(imageData, 5,5);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Normal
OffscreenCanvas

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/146.0.0.0 Safari/537.36

Browser/OS: Chrome 146 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
Normal	175.9 Ops/sec
OffscreenCanvas	89.1 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down the provided JSON and explain what is being tested, compared options, pros and cons of those approaches, and other considerations.

**Benchmark Definition**

The benchmark measures the performance of `ctx.getImageData` and `putImageData` operations in two scenarios:

1. **Normal**: This test case uses a regular 2D canvas element to render an image using `putImageData`. The canvas is created with a specific size (width = 3460, height = 2160), and the `getImageData` method is called twice: once to create an `ImageData` object and another time to put it back onto the canvas.
2. **OffscreenCanvas**: This test case uses an `OffscreenCanvas` element to render an image using `putImageData`. The offscreen canvas is created with the same size as the normal case, and the same operations are performed.

**Options Compared**

The two options being compared are:

1. Using a regular 2D canvas element (`ctx`) versus
2. Using an `OffscreenCanvas` element (`ctx2`)

**Pros and Cons of Each Approach**

1. **Regular 2D Canvas Element (`ctx`)**:
	* Pros:
		+ Faster rendering, as the image is rendered directly onto the screen.
		+ Easier to debug and visualize performance issues.
	* Cons:
		+ May cause performance issues if not used carefully (e.g., creating too many canvases).
2. **OffscreenCanvas Element (`ctx2`)**:
	* Pros:
		+ Can be used to render images without affecting the screen rendering.
		+ Can help avoid performance issues caused by creating multiple canvases.
	* Cons:
		+ May require additional memory allocation and management.
		+ Can introduce additional overhead due to off-screen rendering.

**Other Considerations**

1. **Library Usage**: Neither test case uses any external libraries or frameworks, which simplifies the comparison between the two approaches.
2. **Special JS Features/Syntax**: None of the benchmark cases use special JavaScript features or syntax that would impact performance.

**Alternatives**

If you want to explore alternative approaches, consider:

1. Using Web Workers: You can create a separate thread to handle image rendering, which can help offload CPU-intensive tasks.
2. Utilizing WebGL: If you need high-performance graphics, you can use WebGL, which is designed for real-time 3D graphics rendering.

Keep in mind that these alternatives may introduce additional complexity and dependencies, so it's essential to evaluate their relevance to your specific use case before implementing them.

Related benchmarks:

OffscreenCanvas GetImageData (version: 0)

OffscreenCanvas GetImageData

Comparing performance of: Normal vs OffscreenCanvas

Created: 4 years ago by: Guest

Jump to the latest result

Normal

OffscreenCanvas

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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