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WebAssembly experiment: C++ vs JS


WebAssembly brings the webapp executes as fast as running machine code. It is now supported in all major browsers (Chrome, Firefox, Edge, Safari). I’m very excited about the potential so I started to evaluate it.

This is an experimental webapp to demonstrate how to call the external C++ module from Javascript. In addition, here also compares the performance for manipulating a list of products in C++ (with STL) versus Javascript (with Lodash).

Contents of this Blog:
  1. Development environment setup
  2. Develop C++ module
  3. Develop the web interface
  4. Develop Javascript module
  5. Performance comparison result

1. Development Environment Setup

In my development environment, I’m using MacOSX 10.11 EI Capitan. The programming language versions I installed as below:
$ node -v
# v8.9.1
$ python -V
# Python 2.7.13
$ java -version
# java version "1.8.0_171"
$ clang++ -v
# clang version 6.0.1  (emscripten 1.38.6 : 1.38.6)
$ cmake -version
# cmake version 3.11.4

Install Visual Studio Code

Visual Studio Code (VSCode) is a light-weight and cross-platform editor. You can download it free from here.

After the VSCode installed, you’ll need to install C/C++ language extension like this screenshot:

Install Emscripten

Emscripten is a source-to-source compiler to compile C++ into WebAssembly.

Follow these instructions to install the Emscripten and its prerequisites.

When I installed the Emscripten. I need to run below commands before using it:
# Make sure at Emscripten installation directory
$ source ./
Below command is to verify the installation:
$ emcc -v
# emcc (Emscripten gcc/clang-like replacement + linker emulating GNU ld) 1.38.6

2. Develop C++ Module

Create the project

Before creating the project, make sure you have run the source ./ in Emscripten directory. Then type this commands:
$ cd ~/code # suppose your codebase in ~/Code
$ mkdir wasm_exp && cd wasm_exp
Create the module files as below:
  1. main.cpp
    • This is the main program file.
    • Create a product array.
    • Operate the product array (two filterings and one sorting).
    • Perform one million times of operations on the product array.
  2. headers.h
    • Include all STL headers. The product array operations are using STL vector.
  3. product.h
    • Declares a product object
  4. product.cpp
    • Operator overloaded function for dumping the product to ostream such as cout.
  5. Makefile

VSCode settings for building and debugging

Now you can run the C++ module inside the VSCode. To do that, create two files: tasks.json & launch.json. VSCode can help you to create the tasks.json. In VScode editor, click menu “Tasks”->”Configure Default Build Task…”->”Create tasks.json file from template”->”Others”. Like the screenshot below:

Replace the tasks.json with below contents:
"version": "2.0.0",
  "tasks": [
      "label": "build",
      "type": "shell",
      "command": "make",
      "args": [ "debug" ],
      "group": {
        "kind": "build",
        "isDefault": true
      "problemMatcher": {
        "owner": "cpp",
        "fileLocation": ["relative", "${workspaceFolder}"],
        "pattern": {
          "regexp": "^(.*):(\\d+):(\\d+):\\s+(warning|error):\\s+(.*)$",
          "file": 1,
          "line": 2,
          "column": 3,
          "severity": 4,
          "message": 5
The next one is to create launch.json for debugging. In VSCode, click “Debug” tab, then select ‘Configure or fix launch.json’ as below screenshot:

Modify the two settings in launch.json:

      "preLaunchTask": "build",
      "program": "${workspaceFolder}/app",

Now you can set a breakpoint in VSCode and start the debugger (press F5). See below screenshot:

Compile the C++ into WASM

Emscripten can compile the C++ module into a single Javascript file which is WASM format. I’ve already created the build script in the Makefile. To build it, type:
$ make wasm
Note: If the build failed, you may forget to run source ./ inside the emsdk directory.

If the build is successful, it generates an app.js and app.wasm files respectively. Actually, we’ll need only the app.js file in the next section.

3. Develop Web Interface

In this section, we’ll develop a simple website to incorporate the app.js which generated by Emscripten. I’m a fan of Semantic UI, so I build the frontend in Semantic UI. All the external dependencies (include frameworks, libraries) retrieve from the CDN.

Click here to view the contents of index.html. Notice that it loads the app.js using async syntax as below:
<script async type="text/javascript" src="app.js"></script>

4. Develop Javascript Module

To make the comparison between WebAssembly and Javascript. I developed a Javascript module that performs the same operations as what the C++ module does. I used Lodash to process the product array. You can view the contents of product.js file. Below is the main operations:
function ProcessProducts() {
  let products = CreateProducts();
  let products1 = _.filter(products, (product) => {
    return product._price >= 20.0 && product._price <= 200.0;
  let products2 = _.filter(products1, (product) => {
    return product._description.includes('pretium');
  let products3 = _.sortBy(products2, '_price');
  return products3;

5. Performance Comparison Result

At this time, we can run a webserver to browse the website to start the comparison. At the project root directory, start the http-server as below commands (if you haven’t installed the http-server, you can install it via npm install -g http-server):
$ http-server
# Starting up http-server, serving ./
# Available on:
Open the Chrome browser (version 57 or above) and browses http://localhost:8080. Below is the website screenshot:

The Results from my PC

You can click C++ and JS execute buttons one by one. Below is the result of my Macbook (2016):

6. Conclusion

As you can see, in this experiment, Javascript out-performs C++ nearly 3 times. This surprised me. It represents Google’s V8 engine is really very fast even faster than C++ STL. But it is just a case of the smaller array sizes. In the results of another experiment, C++ WebAssembly performs faster than Javascript on larger array sizes.

The Source Codes

The source codes are hosting in this Github repo


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