Benchmark: my-test-test1 - MeasureThat.net

HTML Preparation code:

<canvas id="target" width="200" height="200"></canvas>

Script Preparation code:

var imagebase = "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAMgAAADIBAMAAABfdrOtAAAABGdBTUEAALGPC/xhBQAAADBQTFRFgwD/1hCepugQI098S1QpNiMbkGVIsIpry6eMcUQo/gAAAP8B/38AAAD//wD///8BJIDoogAAC9hJREFUeNrtmc9rHMkVx/0P7CEia9aXCJnAGvbgg0lgET5t95hGx+2W3eQUM6pW5SJYdqtb5BA2ZNWdUyDuLqV2F0LAMXiYo29zzzrQ4IMhF2PwXAw5rME+hNw6772qbo2k6VH/yDT5obJHtmTTn3m/vu/VmytvGp9XL7ueK5eQNUHeXFpyCfkvh7x3Cfn/hHzfkfF8CMj2AJDnswEgswEg2wNAns/aQV51NGTtkBezASCzASDbA0Cez1pD3nQ0ZL2QF7P1Q4yz1gvZHgBSGbJOyHY3yHtdor5OyImz1gjZHgCyaMjaINsDQE4ZsibIaUY7yPednLUmyBlD1gPZHgDyYrZ+yFlntYS86uSsdUDOG7IGyPYAkBezvpDnn96i8/HtFs5qB5krV5nz4Ba8bjdzVjvI+5bjqIXDb718+bG6faEhLSBzmRLCUallK2W5iqUv/yZVem707QyZs7FlqVNHMo5fF932oh/kfcvi+tFcKvxFfweXwU/T2yud1Rjy2nUUOUtKBr8ZPltxyRX9NF0V9caQObcIwZQMBCAYk4iQ0tjzYKUhDSGvyzgwFgKEMJxDTMAUCSnH2E/57VpDmkGu8hJRQshjEk0rY/Ptg1pGI8hc567k+PiIIMgxZJXiF0i9nT6QOafHcDLEWEKHL+RzCpRPekBepzq+mFWMBQQxpNOFU2tLA8jfKYkgnSoTRBCEAjm6XDJ8oay5nSFz/TAmDSEARhhGYRhWpmR+ChTXSbtC5hgLqTPLUAQwkpiCo8PiW1nqe0CyOkHmjEMVYCJJskHHHhhJEp5QMuWnXpY5dVFZDbmKDpEoIpIejo+FcITAiKIoFFxbkjlOlvlepmocdmV1Xmm3U0ggEBgGAZQQGfCdKJPYV8rLfD/rArnmUJ5CWilGDHwwGESW0HdMa36mw68s9U1byNWxTlJIYQmQSD9X6JDEgohEIYhje9DM0raQ1OHUODAuAT45jrU1CcU9KE3hRmFsJ3WcnXaQaycNXUp4+3ECvytITBAhqIdpf6GKpW4ryGujr/iSDBghlUekvYWQOGRlVPY8I5QqawcZadFwSLWQEMaQt1FChiAl5CnopaqioqzUWloq9RBODUM3XawR8lOcVCcW3PM8SWkMpeQady2F/Kh2AiJ5Rwr0QIZiFWgbShC3AeJTfsF/SM0Q4CwJypXJn1Z3XF93xJPcrSwZe3gC0gPB9ozVqbUMMpn8YGlupdWgiI0EIcaSEpIRhPyFopORuxxVA5lMlvisZPgSZTjAQjwHiclfKGCgNmUvdusg5zFzR5kJjlyOQQdBOQUZf8EQQpUIk1LV8ushZ0NjvGV7yogjFMiiJfAt/xwYrs8oPSQVTLq8B1eQ06GZ61RB0cMyAVEB9Q0WAw9NC0Oy5+q5hQfCVNVqyKLPeHaSW9pb3HblIgRqHSLvYg4T5RgExkFbfnYBpMLMM9fziODTKBTotx2UkAi1kin8Gc1GmGA6KBdbUoXmh5aPnS6DxioZJfAePtCHJIspIKCVccAzz1U0WkBcfITAPJFebIkOzXysHBgMMowJzo1gCFS3fS8LyoYVgcKENB0JenGVBdgXMt/eaQIBn12zfOzYkFm+T/NJCIlk2/e+OsYsAyNQLBOsTuwoOOiDQgZ6pmgKmSjLtn0PMJmnhSshb+1+JfGpRKGwgPeiGP6ZJgEpIHypu7SfLGE8dnDAyTB9HZobw5gTZO8YOwo8n7yGBkGWgbtCJlIIHhaM3xyiw05pDFeRIIz3INu8kSd1E8Y2rEcJgOD4Almc/hirMbOaQtLUyrzMoxrZxZCUiutizcc4D8X4eIgMGIZVCtL1zRPowi3cRWXoQXr5KpMU95Dc5TKMhzGCWiP+IWA2ZuwXO092ocmlXkPIY0c7ChglRAjIARkkNAOTNbrPgzVJyPE6wXdm/ucMkqspBJ/va91Sx0zquQ67CSZVSD2+7PMxTZUa8gQtaQpRVU/MdDsKdOKSYJ1q8/QDnPBCgqgRb+wumtK1NGIdY5mYxosVstiBNQQvRYzPZk98h6f2J40tcUtDskD3d5IsjIGOBX6N8GtlCbYqx0nVT3aaQdKFW6BP3orM1Ai6GOn3j7lFDIEQeCfUD23OslkziJWir3x9F8S3GVXuik+cFLB9AMUEgTIhCJTKTkOIu7DUkljPAInChYkrFiRWDCUmxNSCakxnK84F7pI0Vuvi0w5DQwRsu0BAj/HvJPZha8ijUzstQUGPzXWBbibh2CaV8VDI6B7Z3pLJ4v2fLm9RaQnpI3UwOndIH0khx20h1bwFVw+h5+wwqiyJo7FheC5BsOJ52hlCFxOUJ53Csblj0Xzqan9FGsJ22kIeOiWhtKS6iyLkiKywkLIfx8aS1hDML1ov4qJO99tFCA6O1tjCwNzDyYjBYGe1hzzmeicHC0AQX2iMWldM3X+BzrLInLsAPmQKMrg9REeFo7sgc3DYOmm3GmLO3Rg3BlCxTgfIQ30jhXGq3AjplQ1l115JsL1RopdFUnWAPFKcFlycLUBQDVFYKggUCoow7l66WIL+ghUA46RdRKE5iCQMAm99akoe3XUcMkvNOkAemn2gFDAfYgoH5dyQJL89iQmt1qBKRrwL5PFI6XWgoCSOQ1oW6FvQkVVVvN61YKl0gUxwS4vLX8F0zeslEQ31VeS9Xdp8YNGPf9kFMtHDI5ZzQOJFxaI7ymEJkfhDsQ+QUXH9ow4Q0BZJm2xGJU+LJ9PhSxV2GcQkFrjEDYqiePdRa8hj8hfcnUWgu3m1LDDzJOQYaAFM9VAo4bcFnnc15tRCJrs0czHaa9HgGAbl8MXHno2GkBZwzK/fF4XBtIO4KX26UA52NEPqcQWUFzTY1f8WKhy8flUUKzD1kNSCq7ViUblGg/nERD6CLepobHG9DBlBvS5AlsWmHjKxFC44w4oSQys3+zTGx+MRx8Ev2LsrZCQOisVzNjQrIC5eOIS5I+DTj0bljhPceLirP0fx7oAbz0DO+mwFJIVCUVTkpaB4xnE4PdierSs/EEF8FnIGswLyZ8hgn5VzCn7Zk6avwHqrqnroN8l5yKnQrICAfqVwP4kqSHzoBlryU/ukb5EeLIEshGYFZALj8NePFoahRGS7eAmldYdrQRnBcHSM2imWQirMKoirvK+nZp8S47ANezRX4t4GtlyUEbDwos19+Mei5ly/CJJ6zmRSboaQkRySm+AiaQIFppB81lliMmAV5KHlTybfVddDvE6jFRpBIhAIXxCk1hLKgFUQPNO/RNWuDl4ojfuhMYzqnWTAOihWnYsg+V/xkb/b0O+dTMHdB4oYdmXhY0ocsaIPZJrnd+DhX269vQEOw1uDZ4/QXbhNh2Q4cqEzJuFnvSB5nmP23N/Y+EDfgI5s12ZkCX4fHLmgZzG72QcChsB5mvx6Y+OtuWbBzoE2njFtieIMNi+hLHpANCPPk83Ng40b6J4oEp4d6CseXr/iMSxDxEEfiGGAKcnPt95u0XPjsRuYGyqMLmIPfHdBRFZDSkPy/LPk+sbmBmYxXuYk7QkQGHEIUHizD6RioClbW5BhtOUaOxIDD86Cid5j8f2iB+SEkX8Xfbmxsbn5AZlymCkSZcCMYekmbvaATE9ByJStf6IqHnps/yhAf8HW+zhgRQ9IvnggxlArmxgVWHaP8MNyUH7bdkJ20AMyPQV5SmK8tXUDdym2Sx9msD3bliEvekDy8yfZxxYSiiyDm6v3h9+4ngrE/R6Q6RLIUywO+KiGwwd9rrU7tpWM5c0ekLz2cFyuwkbT9vGTmQYRqYXUM579A65FsOZwHAe2O02cVQeZ1kPyQly/HtKH53BnKHpA8lUQHA8+xGUx4wc9INOLIMW7D+G6ctjMWTWQ/EIIgYqiByRvBin6QKZDQPIBINMhIPkAkHwAyHQISD4A5GJD8me9IfkAkOkAkCaM3pB8AMh0CEg+AGQ6AKQhox8kHwAyHQKSDwBpbEgXhbzSmtHdkjxfvyXTISD5AJDpAJB2jI6QfADIdAhIPgBkOgQkHwCS/2dCnl1acgm5hFxCLiH/LvH634H8C2Mi15WzTge5AAAAAElFTkSuQmCC";

var image = document.createElement('img');
image.src = imagebase;
var canvas = document.createElement('canvas');
canvas.width = 200;
canvas.height = 200;
var ctx = canvas.getContext('2d');
var imageloaded = false;
var imageBitmap;
image.onload = async function() {
  ctx.drawImage(image, 0, 0);
  imageloaded = true;
  imageBitmap = await createImageBitmap(image)
};

var drawcanvas = document.getElementById('target');
var drawctx = drawcanvas.getContext('2d');

Tests:

test1
drawctx.drawImage(image, 50, 50, 120, 120, 5, 5, 120, 120);
test2
drawctx.drawImage(canvas, 50, 50, 120, 120, 5, 5, 120, 120);
test3
drawctx.drawImage(imageBitmap, 50, 50, 120, 120, 5, 5, 120, 120);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
test1
test2
test3

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

A tough one!

After analyzing the provided data, I'll attempt to identify the underlying issue.

**Observations:**

1. The benchmarking code appears to be using the `drawImage` method of the 2D drawing context (`drawctx`) on a canvas element (`drawcanvas`).
2. There are three test cases with different `drawImage` calls, which seem to be testing various aspects of the image rendering process.
3. The latest benchmark results show varying execution rates for each test case.

**Potential Issue:**

The code creates an image from a URL and then immediately draws it on a canvas using `drawctx.drawImage()`. This can lead to several issues:

* **Memory Leaks**: If the images are not properly cleared or garbage collected, memory leaks might occur.
* **Canvas Context Reset**: Each time `drawctx.drawImage()` is called, it resets the canvas context. This could affect subsequent drawing operations.
* **Browser Cache**: The browser's cache might be influencing the benchmark results. When the same image is drawn multiple times, the browser may reuse the cached version, leading to inaccurate measurements.

**Possible Fix:**

To address these issues, consider the following adjustments:

1. Clear the canvas context before each test case using `drawctx.clearRect()`.
2. Use a unique canvas for each test case to avoid reusing the same context.
3. Avoid drawing images multiple times; instead, use the image directly in the benchmarking code.

Here's an updated version of the HTML preparation code:
```html
<canvas id="target1" width="200" height="200"></canvas>
<canvas id="target2" width="200" height="200"></canvas>
```
And here's an updated version of the JavaScript code:
```javascript
var image = document.createElement('img');
image.src = imagebase;

// Clear canvas context before each test case
function clearCanvas(ctx) {
  ctx.clearRect(0, 0, ctx.canvas.width, ctx.canvas.height);
}

var drawctx1 = document.getElementById('target1').getContext('2d');
var drawctx2 = document.getElementById('target2').getContext('2d');

image.onload = async function() {
  // Use the image directly in the benchmarking code
  // No need to create a new canvas or context

// Test case 1
  clearCanvas(drawctx1);
  drawctx1.drawImage(image, 50, 50, 120, 120);

// Test case 2
  clearCanvas(drawctx2);
  drawctx2.drawImage(image, 150, 50, 120, 120); // Note the offset

// Test case 3 (using imageBitmap)
  clearCanvas(drawctx1);
  drawctx1.drawImage(await createImageBitmap(image), 250, 50, 120, 120);

imageloaded = true;
};
```
Keep in mind that this is just one possible approach to address the potential issues. Further analysis and experimentation may be necessary to determine the root cause of any performance degradation or other concerns.

Latest run results:

Run details: (Test run date: 2 years ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/100.0.4896.127 Safari/537.36

Browser/OS: Chrome 100 on Windows

View result in a separate tab

Test name	Executions per second
test1	345749.0 Ops/sec
test2	381394.5 Ops/sec
test3	346216.2 Ops/sec

Related benchmarks:

my-test-test1 (version: 0)

test

Comparing performance of: test1 vs test2 vs test3

Created: 2 years ago by: Guest

Jump to the latest result

test1

test2

test3

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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