Benchmark: Decoding ascii: TextDecoder vs Js 3

Script Preparation code:

// needed to create bytes array
var encoder = new TextEncoder();
// string length, multiple of 4 - vary to get different results
var n = 192;
var arr = new Uint16Array(n);
for (let i = 0; i < n; ++i) {
  arr[i] = (Math.random() * 0x10000) | 0;
}
var decoder = new TextDecoder();
function decodeNative(arr) {
  return decoder.decode(arr);
}

function decoderJs(buffer) {
  var start = 0;
  var end = buffer.byteLength;

  if (end - start < 1) {
    return "";
  }

  var str = "";
  for (var i = start; i < end;) {
    var t = buffer[i++];

    if (t <= 0x7F) {
      str += String.fromCharCode(t);
    } else if (t >= 0xC0 && t < 0xE0) {
      str += String.fromCharCode((t & 0x1F) << 6 | buffer[i++] & 0x3F);
    } else if (t >= 0xE0 && t < 0xF0) {
      str += String.fromCharCode((t & 0xF) << 12 | (buffer[i++] & 0x3F) << 6 | buffer[i++] & 0x3F);
    } else if (t >= 0xF0) {
      var t2 = ((t & 7) << 18 | (buffer[i++] & 0x3F) << 12 | (buffer[i++] & 0x3F) << 6 | buffer[i++] & 0x3F) - 0x10000;
      str += String.fromCharCode(0xD800 + (t2 >> 10));
      str += String.fromCharCode(0xDC00 + (t2 & 0x3FF));
    }
  }
  return str;
}

Tests:

decodeNative
decodeNative(arr)
decoderJs
decoderJs(arr)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
decodeNative
decoderJs

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/96.0.4664.45 Safari/537.36

Browser/OS: Chrome 96 on Windows

View result in a separate tab

Test name	Executions per second
decodeNative	578444.8 Ops/sec
decoderJs	69940.7 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down the provided benchmarking setup and explore what's being tested, the options compared, pros and cons of each approach, and other considerations.

**Benchmark Overview**

The benchmark measures the performance of ASCII decoding using two different approaches:

1. `decodeNative(arr)`: Using the native `TextDecoder` API.
2. `decoderJs(buffer)`: Implementing a custom JavaScript decoder.

**Options Compared**

The benchmark compares the performance of these two approaches on a variety of string lengths, specifically multiple of 4 (e.g., 192, 384, 512). The goal is to determine which approach is faster for ASCII decoding.

**Pros and Cons of Each Approach**

1. `decodeNative(arr)`:
	* Pros:
		+ Native API, optimized for performance.
		+ Less code to write and maintain.
	* Cons:
		+ Limited control over decoding logic.
2. `decoderJs(buffer)`:
	* Pros:
		+ More control over decoding logic.
		+ Can be written in a specific language or paradigm (e.g., Rust).
	* Cons:
		+ Requires more code to write and maintain.
		+ May not be optimized for performance.

**Library Used**

The `TextDecoder` API is used, which is a part of the Web APIs specification. It's a standardized API for decoding binary data into text strings.

**JavaScript Feature/Syntax**

There are no specific JavaScript features or syntaxes being tested in this benchmark. However, it's worth noting that the custom decoder implementation uses JavaScript-specific techniques like string manipulation and bitwise operations.

**Other Considerations**

* The benchmark assumes a Windows 10 desktop environment with Chrome 96 as the browser.
* The `TextEncoder` API is used to create a bytes array for testing.
* The test cases use `Uint16Array` to simulate different string lengths.
* The benchmark measures executions per second, which provides an estimate of performance.

**Alternatives**

If you want to explore alternative approaches, consider the following:

1. **Native C++ or Rust**: Write a native decoder in C++ or Rust for better performance.
2. **WebAssembly (WASM)**: Compile your custom decoder to WASM and run it in a browser.
3. **Custom JavaScript library**: Create a dedicated JavaScript library for decoding binary data.

Keep in mind that each alternative approach has its own set of trade-offs, including increased complexity, performance overhead, or compatibility issues.

Related benchmarks:

Decoding ascii: TextDecoder vs Js 3 (version: 0)

Measure performance of ascii decoding for various string lengths.

Comparing performance of: decodeNative vs decoderJs

Created: 3 years ago by: Guest

Jump to the latest result

decodeNative

decoderJs

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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