Benchmark: Float64 vs Array

Script Preparation code:

var length = 1e6;

var f32_a = Float32Array.from({length}, Math.random);
var f32_b = Float32Array.from({length}, Math.random);

var f64_a = Float64Array.from({length}, Math.random);
var f64_b = Float64Array.from({length}, Math.random);

var arr_a = Array.from({length}, Math.random);
var arr_b = Array.from({length}, Math.random);

Tests:

f32 iterate
for (var i = 0; i < length; i++) { f32_b[i] = f32_a[i]; }
f32 set
f32_b.set(f32_a);
f64 iterate
for (var i = 0; i < length; i++) { f64_b[i] = f64_a[i]; }
f64 set
f64_b.set(f64_a);
arr iterate
for (var i = 0; i < length; i++) { arr_b[i] = arr_a[i]; }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
f32 iterate
f32 set
f64 iterate
f64 set
arr iterate

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

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

LLMs can make mistakes. Check important info.

Measuring JavaScript performance is crucial for creating efficient and scalable web applications.

**Benchmark Context**

The provided benchmark tests the performance of different approaches to work with floating-point numbers (Float64) in JavaScript, specifically using `Float32Array` and `Array`. The tests are designed to measure the time taken by each approach to iterate through an array or perform a set operation on a typed array.

**Options Compared**

There are four options being compared:

1. **Iterating through Float64Array**: This approach uses a traditional for loop to iterate through the elements of the `Float64Array`.
2. **Setting Float32Array**: This approach uses the `set()` method to populate a `Float32Array` from another typed array.
3. **Iterating through Array**: This approach uses a traditional for loop to iterate through the elements of an `Array`.
4. **Setting Array**: This approach uses the `set()` method to populate an `Array` from another typed array.

**Pros and Cons**

1. **Iterating through Float64Array**:
	* Pros: Can be faster than using a traditional for loop, as it leverages SIMD (Single Instruction, Multiple Data) instructions.
	* Cons: Requires the use of a specialized typed array (`Float64Array`), which may not be supported by older browsers or Node.js versions.
2. **Setting Float32Array**:
	* Pros: Faster than iterating through the array using a traditional for loop, as it avoids unnecessary copies and uses SIMD instructions.
	* Cons: Requires the use of a specialized typed array (`Float32Array`), which may not be supported by older browsers or Node.js versions.
3. **Iterating through Array**:
	* Pros: Widely supported by most modern browsers and Node.js versions, as it uses standard JavaScript features.
	* Cons: May be slower than using a specialized typed array like `Float64Array`, due to the overhead of JavaScript operations.
4. **Setting Array**:
	* Pros: Faster than iterating through an array using a traditional for loop, as it avoids unnecessary copies and uses SIMD instructions.
	* Cons: Requires the use of a standard JavaScript array (`Array`), which may not be as efficient as specialized typed arrays.

**Library Used**

None are explicitly mentioned in the provided benchmark definition. However, `Float32Array` and `Float64Array` are built-in typed arrays in JavaScript, while `Array` is a standard JavaScript collection type.

**Special JS Features or Syntax**

The benchmark uses modern JavaScript features such as:

* Typed arrays (`Float32Array`, `Float64Array`)
* ECMAScript 2015+ syntax (e.g., `var`, `let`, `const`, arrow functions)

However, it does not use any experimental or proprietary features.

**Alternatives**

If you need to optimize performance in a JavaScript application, consider the following alternatives:

1. **WebAssembly**: Compile your code to WebAssembly (WASM) and run it in a browser or Node.js environment. WASM provides direct access to hardware resources and can be optimized for performance.
2. **Native modules**: Use native modules (e.g., `ffi` in Node.js) to interact with native code, which can provide better performance than JavaScript-only solutions.
3. **SIMD libraries**: Utilize SIMD libraries like WebAssembly's SIMD instructions or third-party libraries like MathJS or BigFloat for high-performance numerical computations.

Keep in mind that the choice of optimization technique depends on your specific use case and requirements.

Related benchmarks:

Float64 vs Array (version: 0)

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Comparing performance of: f32 iterate vs f32 set vs f64 iterate vs f64 set vs arr iterate

Created: 2 years ago by: Guest

Jump to the latest result

f32 iterate

f32 set

f64 iterate

f64 set

arr iterate

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):