Benchmark: Array vs TypedArray read performance

Tests:

Array write
var array = new Array(100000) let x for (let i=0; i<array.length; i++) { x = array[i] }
TypedArray write
var typedArray = new Uint8Array(100000) let x for (let i=0; i<typedArray.length; i++) { x = typedArray[i] }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Array write
TypedArray write

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 9 months ago)

User agent: Mozilla/5.0 (iPhone; CPU iPhone OS 18_5 like Mac OS X) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/18.5 Mobile/15E148 Safari/604.1

Browser/OS: Mobile Safari 18 on iOS 18.5

View result in a separate tab

Test name	Executions per second
Array write	12478.9 Ops/sec
TypedArray write	23568.1 Ops/sec

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

LLMs can make mistakes. Check important info.

The provided benchmark compares the performance of reading data from two types of arrays in JavaScript: standard JavaScript arrays (`Array`) and typed arrays (`TypedArray`, specifically `Uint8Array`).

### Options Compared

1. **Array**:
   - **Test Case**: This benchmark reflects a performance assessment of reading from a standard array, created using `new Array(100000)`. 
   - **Method**: It iterates through the array, accessing each element and assigning it to variable `x`.

2. **TypedArray**:
   - **Test Case**: This evaluates the performance of reading from a typed array created with `new Uint8Array(100000)`.
   - **Method**: Similar to the standard array, it iterates through the typed array and assigns each element to `x`.

### Pros and Cons

#### Standard JavaScript Arrays:
- **Pros**:
  - Flexible in terms of types: can hold items of any type (e.g., numbers, strings, objects, etc.).
  - More features available, such as methods for easy manipulation (e.g., `map`, `filter`, etc.).

- **Cons**:
  - Generally slower for numeric operations and large datasets since they have additional overhead to accommodate mixed data types and dynamic resizing.
  - Memory usage can be less efficient as they are not optimized for specific data types.

#### Typed Arrays:
- **Pros**:
  - Optimized for performance with numeric data: designed to handle large volumes of numeric data efficiently.
  - Better memory performance for numeric data as they store elements in a contiguous memory block.
  - Provides a more predictable access speed, especially significant for performance-sensitive applications, such as graphics processing or high-performance computing.

- **Cons**:
  - Limited to specific data types (e.g., `Uint8Array` stores unsigned 8-bit integers only).
  - Lacks some of the convenience features present in standard arrays (like built-in methods for manipulation).

### Other Considerations

- **Performance Metrics**: The benchmark results show the number of executions per second for each type of array when reading data.
  - **Array**: 15,593.74 executions per second.
  - **TypedArray**: 15,209.17 executions per second.
  - While the standard array performed better in this particular test, the performance characteristics can vary depending on the use case and the specific operations being executed.

- **Use Cases**: 
  - Use standard arrays when flexibility is required and you don’t need to maximize speed for numeric calculations.
  - Opt for typed arrays when working with large sets of numerical data that demand high performance, especially in applications like WebGL, data processing, or when interfacing with binary data.

### Alternatives
1. **Regular JS Objects**: Used for key-value pairs but not optimal for indexed collections.
2. **Set and Map**: More suitable for unique values and key-value pairs but also not optimized for indexed access.
3. **More Complex Data Structures**: Like linked lists, trees, or other custom structures, which may be more appropriate depending on the specific needs of the application.

In conclusion, the choice between a standard array and a typed array depends on the specific use case, data types involved, and performance requirements. Each has its benefits and drawbacks, making your task a matter of assessing the context in which they will be applied.

Related benchmarks:

Array vs TypedArray read performance (version: 1)

Comparing performance of: Array write vs TypedArray write

Created: one year ago by: Guest

Jump to the latest result

Array write

TypedArray write

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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