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Float64 vs Array
(version: 0)
Blah
Comparing performance of:
f32 iterate vs f32 set vs f64 iterate vs f64 set vs arr iterate
Created:
2 years ago
by:
Guest
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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>
Run tests (5)
Previous results
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Test case name
Result
f32 iterate
f32 set
f64 iterate
f64 set
arr iterate
Fastest:
N/A
Slowest:
N/A
Latest run results:
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Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
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.
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