Benchmark: Do TypedArrays slow down when you add attributes to them?

Script Preparation code:

var array = new Float32Array(10000);
var array_with_attributes = new Float32Array(10000);
array_with_attributes.foo = 1;

Tests:

without attributes
for (var i = 0, li = array.length; i < li; i++) { array[i] = i; }
with attributes
for (var i = 0, li = array_with_attributes.length; i < li; i++) { array_with_attributes[i] = i; }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
without attributes
with attributes

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 8 years ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/53.0.2785.143 Safari/537.36

Browser/OS: Chrome 53 on Mac OS X 10.11.6

View result in a separate tab

Test name	Executions per second
without attributes	1115.5 Ops/sec
with attributes	1115.4 Ops/sec

Autogenerated LLM Summary (model llama3.2:3b, generated 6 months ago):

LLMs can make mistakes. Check important info.

Let's break down the benchmark and explain what's being tested.

**What is tested:**

The provided JSON represents a JavaScript microbenchmark that compares the performance of two approaches:

1. **TypedArray without attributes**: This test measures the time it takes to populate a TypedArray (a typed, homogeneous array) with values.
2. **TypedArray with attributes**: This test measures the time it takes to populate a TypedArray with values and add an attribute (in this case, a simple property `foo`) to the array.

**Options compared:**

The two tests use the same underlying data structure (a Float32Array), but differ in how they handle adding attributes to the array. The first test does not add any attributes to the array, while the second test adds an attribute (`foo = 1`).

**Pros and cons of each approach:**

* **Without attributes**:
	+ Pros: Simple, straightforward implementation; likely to be faster since it doesn't incur the overhead of adding a property.
	+ Cons: No additional functionality is added to the array, which might not be desirable in some scenarios.
* **With attributes**:
	+ Pros: Allows for easy addition of custom properties or behavior to the array.
	+ Cons: May introduce additional overhead due to the property lookup and assignment.

In general, adding attributes to a TypedArray can be useful when working with complex data structures, but it may come at the cost of performance. The benchmark helps to quantify this trade-off.

**Library usage:**

There is no explicit library mentioned in the provided code snippets. However, TypedArrays are a built-in JavaScript feature, introduced in ECMAScript 5 (ES5).

**Special JS features or syntax:**

None are explicitly used in the provided code snippets. However, it's worth noting that some modern JavaScript features like `let` and `const` declarations may be used implicitly due to function scoping (e.g., `var i = 0;`). But this is not relevant to the specific benchmark.

**Other alternatives:**

If you wanted to run a similar benchmark with different options, here are some alternative approaches:

* **Without attributes**: Use a simple array instead of a TypedArray.
* **With attributes**: Add multiple properties or use a more complex data structure (e.g., an object) to populate the array.
* **Using a library**: Consider using a library like Lodash or Underscore.js, which provide utilities for working with arrays and objects. This could introduce additional overhead but may also simplify the code.

Keep in mind that these alternatives would change the fundamental nature of the benchmark, so it's essential to carefully consider the goals and requirements of your testing when exploring different approaches.

Related benchmarks:

Do TypedArrays slow down when you add attributes to them? (version: 0)

Comparing performance of: without attributes vs with attributes

Created: 8 years ago by: Registered User

Jump to the latest result

without attributes

with attributes

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 6 months ago):