Benchmark: tailnh-test - MeasureThat.net

HTML Preparation code:

<canvas id="mycanvas" width="300" height="265" style='background: green'></canvas>

<img id="myimage" width="256" height="256" alt='' src='#' style='background: gray'></img>

Script Preparation code:

var i1 = "https://wallpapers.com/images/hd/abstract-background-6m6cjbifu3zpfv84.jpg"
var i2 = "https://bulma.io/images/placeholders/256x256.png"
var img1 = new Image()
img1.src = i1;

var img2 = new Image()
img2.src = i2;

var canvas = document.getElementById("mycanvas");
var ctx = canvas.getContext('2d');

var img = document.getElementById("myimage");

Tests:

canvas
ctx.drawImage(img1, 0, 0, 256, 256); ctx.drawImage(img2, 0, 0, 256, 256);
img
img.src = i1; img.src = i2;

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
canvas
img

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

This benchmark does not have any results yet. Be the first one to run it!

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

LLMs can make mistakes. Check important info.

I'll break down the provided benchmark and explain what's being tested, compared options, pros and cons of those approaches, and other considerations.

**Benchmark Overview**

MeasureThat.net is a website that allows users to create and run JavaScript microbenchmarks. The provided benchmark defines two test cases: `canvas` and `img`. These tests are used to measure the performance of different browser implementations on various devices.

**Test Case 1: Canvas**

The first test case, "canvas", involves drawing two images on a canvas element using the `drawImage()` method. Specifically, it draws `img1` (a PNG image) and `img2` (another PNG image) with a size of 256x256 pixels at the top-left corner of the canvas.

**Test Case 2: img**

The second test case, "img", involves changing the source URL of an `<img>` element twice. The initial src attribute is set to `i1`, and then immediately changed to `i2`.

**Comparison Options**

In this benchmark, two comparison options are used:

1. **Direct vs. Indirect**: In the "canvas" test case, the images are directly drawn on the canvas using the `drawImage()` method. In contrast, some browsers might use indirect methods (e.g., creating a new `<img>` element and drawing it on the canvas) to achieve similar results.
2. **Sequential vs. Concurrent Execution**: The "img" test case involves executing two consecutive assignments to the `src` attribute of an `<img>` element. This can be compared with concurrent execution, where both assignments might be executed simultaneously.

**Pros and Cons**

Here are some pros and cons of each approach:

1. **Direct vs. Indirect**:
	* Pros: Direct drawing can provide more accurate results, as it's a direct interaction between the browser and the canvas.
	* Cons: Some browsers might use indirect methods to optimize performance or memory usage.
2. **Sequential vs. Concurrent Execution**:
	* Pros: Sequential execution can ensure thread safety and prevent potential concurrency issues.
	* Cons: This approach might lead to slower overall performance, as each assignment is executed separately.

**Library Usage**

In this benchmark, the `Image` object is used to load and manipulate images. The `CanvasRenderingContext2D` API is also utilized for drawing on the canvas element.

**Special JS Features/Syntax**

None of the test cases use any special JavaScript features or syntax that might affect browser behavior.

**Other Considerations**

* **Memory Usage**: The benchmark creates a new image object (`img1` and `img2`) and updates their source URLs, which can impact memory usage.
* **Browser Optimization**: Different browsers might optimize performance by reusing existing resources (e.g., images) or using cache mechanisms to reduce the number of requests.

**Alternatives**

If you wanted to create a similar benchmark, you could consider adding more test cases that:

1. Test other graphics APIs, like WebGL or WebSlices.
2. Involve more complex graphics operations, such as transformations or clipping.
3. Utilize different image formats (e.g., JPEG, GIF) and compression algorithms.
4. Introduce latency or network delays to simulate real-world scenarios.

Keep in mind that the specific test cases and comparisons will depend on your goals and focus areas for your benchmarking project.

Related benchmarks:

tailnh-test (version: 0)

Comparing performance of: canvas vs img

Created: 2 years ago by: Guest

Jump to the latest result

canvas

img

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

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