Benchmark: ES6 Class vs Function with float32array vs Function with Array

Tests:

ES6 Class
class Point { constructor(x, y){ this.x = x; this.y = y; } add(point){ return new Point(this.x + point.x, this.y + point.y); } sub(point){ return new Point(this.x - point.x, this.y - point.y); } } var p1 = new Point(10, 10); var p2 = new Point(10, -10); var sum = p1.add(p2); var dif = p1.sub(p2);
Function float32array
function create_point(x,y){ return new Float32Array([ x , y ]) } function add_points(a,b){ return new Float32Array( [ a[0] + b[0] , a[1] + b[1] ] ) } function sub_points(a,b){ return new Float32Array( [ a[0] - b[0] , a[1] - b[1] ] ); } var p1 = create_point(10,10); var p2 = create_point(10,-10); var sum = add_points(p1,p2); var dif = sub_points(p1,p2);
Function array
function create_point(x,y){ return [ x , y ]; } function add_points(a,b){ return [ a[0] + b[0] , a[1] + b[1] ]; } function sub_points(a,b){ return [ a[0] - b[0] , a[1] - b[1] ]; } var p1 = create_point(10,10); var p2 = create_point(10,-10); var sum = add_points(p1,p2); var dif = sub_points(p1,p2);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
ES6 Class
Function float32array
Function array

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 27 days ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36

Browser/OS: Chrome 131 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
ES6 Class	848341.6 Ops/sec
Function float32array	3845733.8 Ops/sec
Function array	170239040.0 Ops/sec

Autogenerated LLM Summary (model gpt-4o-mini, generated one month ago):

LLMs can make mistakes. Check important info.

This benchmark compares three different approaches for representing and manipulating a point in a two-dimensional space using JavaScript. The tested approaches are:

1. **ES6 Class Method** 
2. **Function using Float32Array**
3. **Function using Regular JavaScript Array**

### Approaches Compared

1. **ES6 Class**
   - **Implementation**: The ES6 class `Point` defines a constructor that initializes x and y coordinates and includes methods for addition and subtraction of points.
   - **Pros**:
     - Object-oriented approach which can encapsulate logic and state more naturally.
     - Methods like `add` and `sub` are inside the `Point` class and can utilize `this`, leading to clearer semantics.
     - Better organization, especially for larger applications or when more methods related to points are needed.
   - **Cons**:
     - Generally slower than simple function calls, particularly in cases where performance is critical.
     - More overhead due to object construction and method invocation.

2. **Function with Float32Array**
   - **Implementation**: This approach uses `Float32Array`, a typed array, to store the x and y coordinates. It uses functions to create points, add, and subtract them.
   - **Pros**:
     - Typed arrays are more efficient in terms of memory management and performance, especially in numerical computations. They provide better performance due to contiguous memory and optimized white space.
     - Ideal for performance-critical applications such as games or simulations where coordinate manipulation is frequent.
   - **Cons**:
     - Less user-friendly compared to objects; the code requires more bookkeeping and sometimes can be less readable.
     - Less extensible, as you can't easily add methods to manipulate points, unlike an ES6 class.

3. **Function with Regular JavaScript Array**
   - **Implementation**: This implementation simply represents the point using a standard array, with functions to create, add, and subtract points.
   - **Pros**:
     - Straightforward and easy to understand; good for quick prototypes or simple applications.
     - Arrays are flexible and allow dynamic size changes.
   - **Cons**:
     - Regular arrays do not enforce type; thus, there's a risk of mistakenly adding or managing different types of data.
     - Performance is relatively poor compared to typed arrays due to the overhead of method calls, and memory may not be as efficient.

### Benchmark Results

The benchmark results show that:

- The **Function with Regular Array** approach outperformed the others significantly, achieving an execution rate of approximately 137 million operations per second.
- The **Function with Float32Array** was a distant second, at about 1.1 million operations per second.
- The **ES6 Class** approach performed the least efficiently, at approximately 346 thousand operations per second.

### Other Considerations
When deciding among these options, the following considerations can be important:

- **Use Case**: If your application requires many mathematical operations with points (like in game development or graphical applications), the function with `Float32Array` is ideal. For applications that favor readability and maintainability, particularly for complex data and behaviors, the ES6 class approach may be preferred.
- **Development Speed**: If the project is intended to be quickly prototyped without heavy performance constraints, regular arrays may suffice.
- **Future Maintenance**: Classes can make code easier to maintain and extend in the long term.

### Alternatives
- **Using Immutable.js or similar libraries**: For working with points while enforcing immutability and potentially providing optimized performance and features for complex data structures.
- **Libraries like math.js**: A mathematical library that provides a comprehensive set of mathematical functions and types, which may offer optimized performance and better functionality for vector and matrix operations.
- **Using WebAssembly**: For performance-intensive applications, leveraging WebAssembly with compiled languages like Rust or C++ can provide a significant performance boost for numerical computations compared to plain JavaScript.

By choosing the right approach based on specific project needs and constraints, developers can optimize for either performance or maintainability as needed.

Related benchmarks:

ES6 Class vs Function with float32array vs Function with Array (version: 1)

Comparing performance of: ES6 Class vs Function float32array vs Function array

Created: one month ago by: Guest

Jump to the latest result

ES6 Class

Function float32array

Function array

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model gpt-4o-mini, generated one month ago):