Benchmark: soa vs aos using Float32Array

Script Preparation code:

var x = new Float32Array(1000000),
    y = new Float32Array(1000000),
    z = new Float32Array(1000000);

var vectors = [];
for (var i = 0; i < 1000000; i++) {
    x[i] = Math.random() * 100 | 0;
    y[i] = Math.random() * 100 | 0;
    z[i] = Math.random() * 100 | 0;

    vectors[i] = {
        x: x[i],
        y: y[i],
        z: z[i]
    };
}
var vector;

Tests:

soa
for (var i = 0, li=x.length; i < li; ++i) { x[i] = 2 * x[i]; y[i] = 2 * y[i]; z[i] = 2 * z[i]; }
aos
for (var i = 0, li=vectors.length; i < li; ++i) { vector = vectors[i]; vector.x = 2 * vector.x; vector.y = 2 * vector.y; vector.z = 2 * vector.z; }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
soa
aos

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 25 days ago):

LLMs can make mistakes. Check important info.

Let's break down the benchmark and its options.

**Benchmark Overview**

The benchmark compares two approaches to perform operations on data:

1. **Statically-Ordered Arrays (SOA)**: This approach uses three separate arrays (`x`, `y`, and `z`) to store the data, with each array containing one dimension of the data.
2. **Access-Oblivious Structure (AOS)**: This approach uses an object array (`vectors`) where each element is an object that contains multiple dimensions of the data.

**Options Compared**

The benchmark compares two specific test cases:

1. `soa`: This test case uses the SOA approach, where three separate arrays are used to store the data.
2. `aos`: This test case uses the AOS approach, where an object array is used to store the data.

**Pros and Cons of Each Approach**

* **SOA (Statically-Ordered Arrays)**:
	+ Pros:
		- Can be more efficient for certain types of operations, as the compiler can optimize better.
		- Typically uses less memory, since each dimension has its own separate array.
	+ Cons:
		- Requires explicit indexing and bounds checking to access elements in the arrays.
		- May lead to slower performance due to additional overhead of accessing multiple arrays.
* **AOS (Access-Oblivious Structure)**:
	+ Pros:
		- Can simplify code, as all operations are performed on a single data structure.
		- Typically uses more memory, since each dimension is stored in the same object.
	+ Cons:
		- May lead to slower performance due to additional overhead of accessing and manipulating objects.
		- Requires careful design to ensure efficient access patterns.

**Library Used**

In this benchmark, no libraries are explicitly mentioned. However, the `Float32Array` constructor is used to create arrays with floating-point data type. This suggests that the benchmark may use Web API (Web Platform Incubator) features for creating and manipulating arrays.

**Special JS Features/Syntax**

This benchmark does not specifically test any special JavaScript features or syntax. It only focuses on comparing two different approaches to perform operations on data.

**Other Alternatives**

Some alternative approaches that could be compared in this benchmark include:

* **Row-Major Layout**: This approach uses a single array with row-major layout, where each element is accessed by a fixed offset from the previous one.
* **Column-Major Layout**: This approach uses a single array with column-major layout, where each element is accessed by a fixed offset from the previous one in the same column.

These alternatives could provide additional insights into performance differences and code complexity for different data structures.

Latest run results:

Run details: (Test run date: 2 years ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10.15; rv:100.0) Gecko/20100101 Firefox/100.0

Browser/OS: Firefox 100 on Mac OS X 10.15

View result in a separate tab

Test name	Executions per second
soa	623.2 Ops/sec
aos	267.6 Ops/sec

Related benchmarks:

soa vs aos using Float32Array (version: 0)

As titled

Comparing performance of: soa vs aos

Created: 2 years ago by: Guest

Jump to the latest result

soa

aos

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 25 days ago):