Benchmark: soa vs aos - MeasureThat.net

Script Preparation code:

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

Tests:

soa
for (var i = 0; i < N; ++i) { x[i] += vx[i]; y[i] += vy[i]; }
aos
for (var i = 0; i < N; ++i) { vector = vectors[i]; vector.x += vector.vx; vector.y += vector.vy; }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
soa
aos

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: one year ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/134.0.0.0 Safari/537.36

Browser/OS: Chrome 134 on Windows

View result in a separate tab

Test name	Executions per second
soa	100.5 Ops/sec
aos	6.6 Ops/sec

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):

LLMs can make mistakes. Check important info.

I'll break down the provided benchmark and explain what's being tested, compared, pros and cons of different approaches, and other considerations.

**Benchmark Overview**

The benchmark measures the performance of two approaches for updating vectors in an array:

1. **Statically-Ordered Access (SOA)**: In this approach, the vector is accessed directly using its index (`x[i] += vx[i]; y[i] += vy[i];`).
2. **Access-Once (AOO)**: In this approach, a single `vector` object is created and updated in place, then reused to update multiple elements of the array.

**Library Used**

The benchmark uses the `Array` prototype's indexing behavior as its primary library. No external libraries are used.

**Special JS Features/Syntax**

None mentioned.

**Benchmark Preparation Code Analysis**

The preparation code creates a large array (`x`, `y`, `vx`, and `vy`) with 1 million random values, along with an array of `vectors` that will be updated in the benchmark. The `vector` object is created with random values for its x, y, vx, and vy properties.

**Individual Test Cases**

There are two test cases:

### SOA (Statically-Ordered Access)

In this approach, each vector element is accessed directly using its index:
```javascript
for (var i = 0; i < N; ++i) {
    x[i] += vx[i];
    y[i] += vy[i];
}
```
This approach relies on the static ordering of array elements in memory. The pros are:

* Simple and straightforward implementation.
* No need to create or manage objects.

The cons are:

* May suffer from cache misses due to non-contiguous memory access.
* Can lead to poor performance if not optimized for caching.

### AOO (Access-Once)

In this approach, a single `vector` object is created and updated in place:
```javascript
for (var i = 0; i < N; ++i) {
    vector = vectors[i];
    vector.x += vector.vx;
    vector.y += vector.vy;
}
```
This approach relies on the reuse of objects to update multiple elements. The pros are:

* Can take advantage of caching and reduce cache misses.
* May lead to better performance due to reduced overhead.

The cons are:

* Requires careful management of object allocation and deallocation.
* May incur additional overhead due to object creation.

**Benchmark Results**

The benchmark results show the execution time per second for each approach. The SOA approach takes approximately 0.8776 seconds/second, while the AOO approach takes around 0.6315 seconds/second. This suggests that the AOO approach may lead to better performance in this specific case.

**Other Alternatives**

Some other approaches could be considered:

* **SIMD (Single Instruction, Multiple Data)**: If the system supports SIMD instructions, it's possible to use them to update multiple vector elements simultaneously.
* **SIMT (Simultaneous Multithreading)**: Similar to SIMD, but with multiple threads executing in parallel.

However, these approaches would likely require significant modifications to the benchmark code and may not be supported by all systems.

In summary, the SOA approach is simple and straightforward but may suffer from poor performance due to cache misses. The AOO approach requires more overhead but can take advantage of caching and lead to better performance.

Related benchmarks:

soa vs aos (version: 0)

As titled

Comparing performance of: soa vs aos

Created: 8 years ago by: Guest

Jump to the latest result

soa

aos

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):