Benchmark: soa vs aos - MeasureThat.net

Script Preparation code:

var N = 1000000;

var x = [], y = [], z = [];

var xt = new Float32Array(1000000);
var yt = new Float32Array(1000000);
var zt = new Float32Array(1000000);

var vectors = [];

for(var i = 0; i < N; i++){
  x[i] = Math.random();
  y[i] = Math.random();
  z[i] = Math.random();
  
  xt[i] = x[i];
  yt[i] = y[i];
  zt[i] = z[i];
  
  vectors[i] = { x: x[i], y: y[i], z: z[i] };
}

var vector;

​x
 
var N = 1000000;​var x = [], y = [], z = [];​var xt = new Float32Array(1000000);var yt = new Float32Array(1000000);var zt = new Float32Array(1000000);​var vectors = [];​for(var i = 0; i < N; i++){  x[i] = Math.random();  y[i] = Math.random();  z[i] = Math.random();    xt[i] = x[i];  yt[i] = y[i];  zt[i] = z[i];    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;
    y[i] *= 2;
    z[i] *= 2;
}

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

aos

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

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

soa mark II

for (var i = 0, li=xt.length; i < li; ++i) {
    xt[i] *= 2;
}
for (var i = 0, li=yt.length; i < li; ++i) {
    yt[i] *= 2;
}
for (var i = 0, li=zt.length; i < li; ++i) {
    zt[i] *= 2;
}

 
for (var i = 0, li=xt.length; i < li; ++i) {    xt[i] *= 2;}for (var i = 0, li=yt.length; i < li; ++i) {    yt[i] *= 2;}for (var i = 0, li=zt.length; i < li; ++i) {    zt[i] *= 2;}

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Experimental features:

Memory measurements supported only in Chrome.
For precise memory measurements Chrome must be launched with --enable-precise-memory-info flag.
More information: Monitoring JavaScript Memory

Test case name	Result
soa
aos
soa mark II

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36

Browser/OS: Chrome 131 on Windows

View result in a separate tab

Test name	Executions per second
soa	146.7 Ops/sec
aos	6.6 Ops/sec
soa mark II	115.2 Ops/sec

Autogenerated LLM Summary (model llama3.2:3b, generated 5 months ago):

Let's dive into the world of JavaScript microbenchmarks on MeasureThat.net.

Benchmark Definition

The benchmark measures the performance difference between two approaches: Staged Operations (SOA) and Staged Array Operations (SAO), also known as Asynchronous Operations (AOs). The benchmark is designed to compare the execution speed of these two approaches in a JavaScript context.

Options Compared

In this benchmark, there are three options being compared:

Staged Operations (SOA): This approach involves executing each stage of the computation separately and then combining the results.
Staged Array Operations (SAO) or Asynchronous Operations (AOs): In this approach, each element of the array is processed asynchronously, which can improve performance by avoiding blocking operations.

Pros and Cons

SOA: Pros:
- Can be more predictable and easier to analyze.
- Allows for better control over the computation pipeline.
Cons:
- May be slower due to the overhead of creating intermediate results.
- Can lead to memory issues if not handled properly.
SAO/AOs: Pros:
- Can provide better performance by avoiding blocking operations.
- Can improve scalability and responsiveness.
Cons:
- Can be more challenging to analyze and debug.
- May require additional infrastructure or libraries to manage asynchronous operations.

Library Used

In the benchmark, the Float32Array class is used to represent large arrays of floating-point numbers. This class provides an efficient way to store and manipulate array data in JavaScript.

Special JS Features/Syntax

There are no special JavaScript features or syntax mentioned in this benchmark. However, it's worth noting that modern JavaScript engines like V8 (used by Chrome) have implemented various optimizations and techniques to improve performance, such as just-in-time compilation and caching.

Other Alternatives

If you're interested in exploring alternative approaches to this benchmark, here are a few options:

Caching: Implementing caching mechanisms can help reduce the overhead of repeated computations.
Parallel Processing: Using parallel processing techniques, like Web Workers or libraries like worker.js, can potentially improve performance by executing computations concurrently.
SIMD Instructions: Using SIMD (Single Instruction, Multiple Data) instructions, like SSE or AVX, can provide significant performance improvements for certain types of computations.

Keep in mind that these alternatives may not be directly applicable to this specific benchmark and may require additional modifications or infrastructure to work effectively.

LLMs can make mistakes. Check important info.

Let's dive into the world of JavaScript microbenchmarks on MeasureThat.net.

**Benchmark Definition**

**Options Compared**

In this benchmark, there are three options being compared:

1. **Staged Operations (SOA)**: This approach involves executing each stage of the computation separately and then combining the results.
2. **Staged Array Operations (SAO) or Asynchronous Operations (AOs)**: In this approach, each element of the array is processed asynchronously, which can improve performance by avoiding blocking operations.

**Pros and Cons**

* **SOA**: Pros:
	+ Can be more predictable and easier to analyze.
	+ Allows for better control over the computation pipeline.
* Cons:
	+ May be slower due to the overhead of creating intermediate results.
	+ Can lead to memory issues if not handled properly.
* **SAO/AOs**: Pros:
	+ Can provide better performance by avoiding blocking operations.
	+ Can improve scalability and responsiveness.
* Cons:
	+ Can be more challenging to analyze and debug.
	+ May require additional infrastructure or libraries to manage asynchronous operations.

**Library Used**

In the benchmark, the `Float32Array` class is used to represent large arrays of floating-point numbers. This class provides an efficient way to store and manipulate array data in JavaScript.

**Special JS Features/Syntax**

**Other Alternatives**

If you're interested in exploring alternative approaches to this benchmark, here are a few options:

1. **Caching**: Implementing caching mechanisms can help reduce the overhead of repeated computations.
2. **Parallel Processing**: Using parallel processing techniques, like Web Workers or libraries like worker.js, can potentially improve performance by executing computations concurrently.
3. **SIMD Instructions**: Using SIMD (Single Instruction, Multiple Data) instructions, like SSE or AVX, can provide significant performance improvements for certain types of computations.

Keep in mind that these alternatives may not be directly applicable to this specific benchmark and may require additional modifications or infrastructure to work effectively.

Related benchmarks:

soa vs aos (version: 0)

As titled

Comparing performance of: soa vs aos vs soa mark II

Created: 8 years ago by: Guest

Jump to the latest result

soa

aos