Benchmark: Canvas cache or Path 2D (updated++)

HTML Preparation code:

<canvas height="500" width="500"></canvas>
<canvas height="500" width="500"></canvas>

AخA
 
<canvas height="500" width="500"></canvas>
<canvas height="500" width="500"></canvas>

Script Preparation code:

var [canvas1, canvas2] = Array.from(document.querySelectorAll('canvas'));
var ctx1 = canvas1.getContext('2d')
var ctx2 = canvas2.getContext('2d')
var rects = new Array(100).fill(null).map(() => ({
    x: Math.floor(Math.random() * 100),
    y: Math.floor(Math.random() * 100),
    width: Math.floor(Math.random() * 100) + 1,
    height: Math.floor(Math.random() * 100) + 1
}))

 
var [canvas1, canvas2] = Array.from(document.querySelectorAll('canvas'));var ctx1 = canvas1.getContext('2d')var ctx2 = canvas2.getContext('2d')var rects = new Array(100).fill(null).map(() => ({    x: Math.floor(Math.random() * 100),    y: Math.floor(Math.random() * 100),    width: Math.floor(Math.random() * 100) + 1,    height: Math.floor(Math.random() * 100) + 1}))

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 = 'blue'
  rect.cached.fillRect(0, 0, rect.width, rect.height)
  ctx1.drawImage(rect.cached.canvas, rect.x, rect.y, rect.width, rect.height)
}

ctx1.clearRect(0, 0, 500, 500)

for (var rect of rects) {
  ctx1.drawImage(rect.cached.canvas, rect.x, rect.y, rect.width, rect.height)
}

​x
 
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 = 'blue'  rect.cached.fillRect(0, 0, rect.width, rect.height)  ctx1.drawImage(rect.cached.canvas, rect.x, rect.y, rect.width, rect.height)}​ctx1.clearRect(0, 0, 500, 500)​for (var rect of rects) {  ctx1.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(rect.x, rect.y, rect.width, rect.height)
  ctx2.fillStyle = rect.fill
  ctx2.fill(rect.path)
}

ctx2.clearRect(0, 0, 500, 500)

for (var rect of rects) {
  ctx2.fillStyle = 'red'
  ctx2.fill(rect.path)
}

 
for (var rect of rects) {  rect.path = new Path2D()  rect.path.rect(rect.x, rect.y, rect.width, rect.height)  ctx2.fillStyle = rect.fill  ctx2.fill(rect.path)}​ctx2.clearRect(0, 0, 500, 500)​for (var rect of rects) {  ctx2.fillStyle = 'red'  ctx2.fill(rect.path)}

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Experimental features:

Memory measurements supported only in Chrome.
For precise memory measurements Chrome must be launched with --enable-precise-memory-info flag.
More information: Monitoring JavaScript Memory

Test case name	Result
Cached canvas
Cached Path2D

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (X11; FreeBSD amd64; rv:97.0) Gecko/20100101 Firefox/97.0

Browser/OS: Firefox 97 on FreeBSD

View result in a separate tab

Test name	Executions per second
Cached canvas	201.3 Ops/sec
Cached Path2D	1711.3 Ops/sec

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

What is being tested?

The provided JSON represents two benchmark test cases for measuring the performance of two different approaches: using cached canvas context and using Path2D.

Options compared:

Two options are being compared:

Cached Canvas: This approach creates a separate canvas element, creates a 2D drawing context (ctx) on that canvas, and then draws rectangles from an array onto the canvas.
Cached Path2D: This approach uses the Path2D API to define a path for each rectangle in the array, which is then filled with a fill color.

Pros and Cons of each approach:

Cached Canvas:

Pros:

Can be faster since it avoids the overhead of creating a new canvas element.
Allows for direct access to the canvas context.

Cons:

Requires an extra DOM element creation, which can be expensive.
May require additional memory allocation.

Cached Path2D:

Pros:

Avoids the overhead of creating a separate canvas element.
Is generally more concise and easier to read.

Cons:

May incur additional overhead due to the Path2D API's complexity.

Other considerations:

The use of Array.from(document.querySelectorAll('canvas')) suggests that this benchmark is designed to test performance in a real-world scenario, where multiple canvas elements may be present.
The use of FreeBSD as an operating system and rv:97.0 as the Firefox version indicates that this benchmark may be targeting specific hardware configurations or versions.

Library and its purpose:

The Path2D API is a part of the HTML5 standard, introduced in 2011. Its primary purpose is to allow for more efficient rendering of complex paths by breaking them down into individual path commands. In this benchmark, it's used to define a path for each rectangle in the array.

Special JS feature or syntax:

None mentioned in the provided code snippets.

Alternative approaches:

Other possible approaches that could be compared in this benchmark include:

Using an image instead of creating multiple rectangles
Using a different drawing method (e.g., SVG)
Implementing a custom caching mechanism for canvas context
Comparing performance with different canvas sizes or resolutions

Keep in mind that the specific alternatives will depend on the goals and requirements of the benchmark.

LLMs can make mistakes. Check important info.

**What is being tested?**

The provided JSON represents two benchmark test cases for measuring the performance of two different approaches: using cached canvas context and using Path2D.

**Options compared:**

Two options are being compared:

1. **Cached Canvas**: This approach creates a separate `canvas` element, creates a 2D drawing context (`ctx`) on that canvas, and then draws rectangles from an array onto the canvas.
2. **Cached Path2D**: This approach uses the `Path2D` API to define a path for each rectangle in the array, which is then filled with a fill color.

**Pros and Cons of each approach:**

**Cached Canvas:**

Pros:

* Can be faster since it avoids the overhead of creating a new canvas element.
* Allows for direct access to the canvas context.

Cons:

* Requires an extra DOM element creation, which can be expensive.
* May require additional memory allocation.

**Cached Path2D:**

Pros:

* Avoids the overhead of creating a separate canvas element.
* Is generally more concise and easier to read.

Cons:

* May incur additional overhead due to the `Path2D` API's complexity.

**Other considerations:**

* The use of `Array.from(document.querySelectorAll('canvas'))` suggests that this benchmark is designed to test performance in a real-world scenario, where multiple canvas elements may be present.
* The use of `FreeBSD` as an operating system and `rv:97.0` as the Firefox version indicates that this benchmark may be targeting specific hardware configurations or versions.

**Library and its purpose:**

The `Path2D` API is a part of the HTML5 standard, introduced in 2011. Its primary purpose is to allow for more efficient rendering of complex paths by breaking them down into individual path commands. In this benchmark, it's used to define a path for each rectangle in the array.

**Special JS feature or syntax:**

None mentioned in the provided code snippets.

**Alternative approaches:**

Other possible approaches that could be compared in this benchmark include:

* Using an image instead of creating multiple rectangles
* Using a different drawing method (e.g., SVG)
* Implementing a custom caching mechanism for canvas context
* Comparing performance with different canvas sizes or resolutions

Keep in mind that the specific alternatives will depend on the goals and requirements of the benchmark.

Related benchmarks:

Canvas cache or Path 2D (updated++) (version: 0)

Comparing performance of: Cached canvas vs Cached Path2D

Created: 3 years ago by: Registered User

Jump to the latest result

Cached canvas

Cached Path2D

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):