Benchmark: Item getting in typed array vs simple array

Script Preparation code:

var size = 1024;
var typedArray = new Float64Array(size);
var array = new Array(size);

for(let i = 0; i < size; i++) {
  typedArray[i] = Math.random();
  array[i] = Math.random();
}

Tests:

typedArray
const a = typedArray[Math.round(Math.random() * size)]
array
const a = array[Math.round(Math.random() * size)]

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
typedArray
array

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 27 days ago):

LLMs can make mistakes. Check important info.

Let's dive into the world of JavaScript microbenchmarks!

**What is being tested?**

The provided JSON represents two test cases that compare the performance of accessing elements in typed arrays versus simple arrays. Specifically, the tests measure how fast it is to retrieve an element from each type of array using a mathematical expression.

**Options compared:**

There are two options being compared:

1. **Typed Arrays**: Typed arrays are a collection of values of the same type, such as `Float64Array` or `IntArray`. They offer several benefits over traditional JavaScript arrays, including:
	* Improved memory efficiency
	* Better performance for numerical computations
	* Simplified data types (e.g., no need to check type explicitly)
2. **Simple Arrays**: Simple arrays are the traditional JavaScript array data structure.

**Pros and Cons:**

**Typed Arrays:**

Pros:

* Improved memory efficiency, which can lead to better performance
* Simplified data types, making code easier to read and write

Cons:

* May not be compatible with older browsers or environments that don't support typed arrays
* Can be slower in certain situations (e.g., when dealing with large datasets)

**Simple Arrays:**

Pros:

* Wide compatibility across browsers and environments
* Often faster for small to medium-sized datasets

Cons:

* More verbose code, requiring explicit type checking
* May lead to memory inefficiencies for large datasets

**Other Considerations:**

When choosing between typed arrays and simple arrays, consider the specific requirements of your project. If you're working with numerical computations or need improved memory efficiency, typed arrays might be a better choice. However, if compatibility is crucial or performance isn't a top priority, simple arrays may be sufficient.

**Library Used:**

The `Float64Array` constructor is used in the benchmark to create a typed array of 64-bit floating-point numbers. This library provides an efficient way to work with large numerical datasets.

**Special JS Feature/Syntax:**

None mentioned in this specific benchmark. However, some other notable features and syntax include:

* **let` and `const`: Block-scoped variables that ensure variable hoisting is only executed once.
* **Arrow Functions`: Simplified function expressions that eliminate the need for explicit `function` declarations.

**Alternative Benchmarking Frameworks:**

If you're interested in exploring alternative benchmarking frameworks, consider the following options:

1. **BenchMarkDotJS**: A popular open-source benchmarking framework for JavaScript.
2. **Benchmark.js**: Another widely-used framework for writing and running benchmarks.
3. **JSDOM`: A JavaScript implementation of the DOM, which can be used for testing and benchmarking web applications.

These frameworks offer features like automatic test case generation, parallel execution, and detailed profiling, making it easier to write efficient and reliable benchmarks.

Latest run results:

Run details: (Test run date: 22 days ago)

User agent: Mozilla/5.0 (X11; Linux x86_64; rv:131.0) Gecko/20100101 Firefox/131.0

Browser/OS: Firefox 131 on Linux

View result in a separate tab

Test name	Executions per second
typedArray	2445493504.0 Ops/sec
array	563880512.0 Ops/sec

Related benchmarks:

Item getting in typed array vs simple array (version: 0)

Comparing performance of: typedArray vs array

Created: 3 years ago by: Guest

Jump to the latest result

typedArray

array

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 27 days ago):