Benchmark: Canvas cache or Path 2D

HTML Preparation code:

<canvas/>

Script Preparation code:

var canvas = document.querySelector('canvas');
var ctx = canvas.getContext('2d')
var rects = new Array(100).fill({ x: 100, y: 100, width: 100, height: 100, fill: 'blue' })

Tests:

Cached canvas
for (var rect of rects) { var cached = document.createElement('canvas') cached.width = rect.width cached.height = rect.height rect.cached = cached.getContext('2d') rect.cached.fillStyle = rect.fill rect.cached.fillRect(0, 0, rect.width, rect.height) ctx.drawImage(rect.cached.canvas, rect.x, rect.y, rect.width, rect.height) } for (var rect of rects) { ctx.drawImage(rect.cached.canvas, rect.x, rect.y, rect.width, rect.height) }
Cached Path2D
for (var rect of rects) { rect.path = new Path2D() rect.path.rect(0, 0, rect.width, rect.height) ctx.fillStyle = rect.fill ctx.fill(rect.path) } for (var rect of rects) { ctx.fillStyle = rect.fill ctx.fill(rect.path) }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Cached canvas
Cached Path2D

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 4 months ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/143.0.0.0 Safari/537.36

Browser/OS: Chrome 143 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
Cached canvas	61.4 Ops/sec
Cached Path2D	11635.1 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 benchmark and explain what is being tested, compared, and their pros/cons.

**Benchmark Overview**

The provided benchmark tests two approaches to rendering rectangles on a 2D context: `Cached Canvas` and `Cached Path2D`. Both approaches aim to measure the performance difference between creating a cache for each rectangle and reusing it during drawing.

**Script Preparation Code**

The script preparation code creates:

1. A canvas element (`<canvas/>`) in the HTML.
2. A 2D context (`ctx`) from the canvas.
3. An array of 100 rectangles with fixed properties (x, y, width, height, and fill color).
4. Assigns each rectangle a `cached` property that will be used to store the result of creating a new `canvas` element.

**Html Preparation Code**

The HTML preparation code only includes the `<canvas/>` element.

**Test Cases**

There are two test cases:

1. **Cached Canvas**: This approach creates a separate `canvas` element for each rectangle and stores its 2D context in the `cached` property of each rectangle. It then draws each rectangle using the original canvas's 2D context.
	* Pros:
		+ Easy to implement and understand.
		+ No additional dependencies required.
	* Cons:
		+ Creates a separate `canvas` element for each rectangle, which may lead to memory issues.
		+ Does not take advantage of cache-friendliness.
2. **Cached Path2D**: This approach uses the `Path2D` object to create and store a path for each rectangle. It then draws each rectangle using this cached path.
	* Pros:
		+ Can be more efficient than creating separate `canvas` elements, as it reuses memory.
	* Cons:
		+ May require additional dependencies (e.g., the `Path2D` API).
		+ More complex implementation compared to the `Cached Canvas` approach.

**Library Usage**

In both test cases, no external libraries are used. However, if you were to use a library like Fabric.js or Paper.js for more complex 2D rendering tasks, their APIs and performance characteristics might be considered in your benchmarking process.

**Special JS Features/Syntax**

There are no specific JavaScript features or syntax mentioned in the provided code. The focus is on comparing two approaches to rendering rectangles using standard JavaScript and canvas API.

**Other Alternatives**

Alternative approaches to rendering rectangles include:

1. **Image-based rendering**: Instead of creating a separate `canvas` element for each rectangle, you could store a small image (e.g., 16x16 pixels) that represents the filled area.
2. **Indexed Canvas**: This approach uses an indexed canvas, which allows storing only the relevant data and avoiding unnecessary allocation of memory.
3. **Canvas pooling**: Similar to `Cached Canvas`, this approach creates a pool of available canvases and assigns them to rectangles on demand.

Keep in mind that these alternative approaches might not be directly comparable to the provided benchmark, as they may require additional dependencies or more complex implementations.

In conclusion, the provided benchmark compares two approaches to rendering rectangles using canvas: creating separate `canvas` elements (`Cached Canvas`) versus using a cached `Path2D` object. The pros and cons of each approach are discussed, considering factors such as memory usage, complexity, and performance characteristics.

Related benchmarks:

Canvas cache or Path 2D (version: 0)

Comparing performance of: Cached canvas vs Cached Path2D

Created: 4 years ago by: Guest

Jump to the latest result

Cached canvas

Cached Path2D

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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