Benchmark: Random I/O various arrays

Script Preparation code:

var a1 = new Array(100000);
var a2 = new Array(100000);
var a3 = new Float64Array(100000);

for (let i = 0; i < 100000; ++i) {
  const x = Math.random();
  a1[i] = x < 0.5 ? Math.random().toString() : x;
  a2[i] = Math.random();
  a3[i] = Math.random();
}

Tests:

mixed use array
for (let i = 0; i < 10000; ++i) { const m = (Math.random() * 10000) | 0; a1[m] = a1[m] + Math.random(); }
single use array
for (let i = 0; i < 10000; ++i) { const m = (Math.random() * 10000) | 0; a2[m] = a2[m] + Math.random(); }
typed array
for (let i = 0; i < 10000; ++i) { const m = (Math.random() * 10000) | 0; a3[m] = a3[m] + Math.random(); }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
mixed use array
single use array
typed array

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 4 months ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:146.0) Gecko/20100101 Firefox/146.0

Browser/OS: Firefox 146 on Windows

View result in a separate tab

Test name	Executions per second
mixed use array	302.8 Ops/sec
single use array	4812.1 Ops/sec
typed array	6436.3 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark definitions and explain what's being tested, compared, and their pros and cons.

**Benchmark Definition**

The first part is the benchmark definition in JSON format, which represents a JavaScript microbenchmark. Here's a summary of what's being tested:

* The script preparation code initializes three arrays: `a1`, `a2`, and `a3`. These arrays will be used to test different aspects of JavaScript.
	+ `a1` is an array of strings with random values, where each value has an equal chance of being a string or an integer.
	+ `a2` is an array of numbers with random values.
	+ `a3` is a typed array (specifically, a Float64Array) of numbers with random values.

The script preparation code also includes a loop that populates these arrays with 100,000 elements each.

**Individual Test Cases**

There are three test cases defined:

1. **Mixed use array**: This test case iterates over the first 10,000 elements of `a1` and updates the corresponding element in `a2`. The index is generated using `Math.random() * 10000 | 0`, which gives a random integer between 0 and 9,999.
	* Pros: Simple to understand and implement, allows for easy testing of array manipulation techniques.
	* Cons: May not accurately represent real-world scenarios where arrays are frequently updated or modified.
2. **Single use array**: This test case is similar to the mixed use array test case, but it updates the corresponding element in `a3` instead of `a2`. The only difference is that the index generated using `Math.random() * 10000 | 0` is now used for both arrays.
	* Pros: Similar pros and cons as the mixed use array test case, with an additional consideration that the typed array may have performance advantages due to its memory management capabilities.
3. **Typed array**: This test case iterates over the first 10,000 elements of `a3` (the Float64Array) and updates the corresponding element in `a1`. The index is generated using `Math.random() * 10000 | 0`, just like in the mixed use array test case.
	* Pros: Allows for testing of performance aspects related to typed arrays, which can provide better memory management and faster access to elements compared to regular arrays.
	* Cons: May require more complex implementation details due to the specifics of Float64Array operations.

**Library**

There is no explicit library mentioned in the benchmark definition or test cases. However, it's worth noting that the `Float64Array` type is a built-in JavaScript type introduced in ECMAScript 2015 (ES6).

**Special JS Feature/Syntax**

None of the test cases explicitly use any special JavaScript features or syntax beyond standard array manipulation and iteration techniques.

**Other Alternatives**

To measure performance differences between these tests, other alternatives could be explored:

* Using different array sizes or data distribution to simulate real-world scenarios.
* Adding more complex operations, such as sorting, filtering, or merging arrays, to the test cases.
* Using specialized libraries like `Benchmark` or `micro-benchmark` for more accurate and controlled performance measurements.
* Running tests on different browsers, devices, or environments to explore platform-specific optimizations.

Keep in mind that the primary goal of this benchmark is to compare the performance differences between using regular arrays versus typed arrays.

Related benchmarks:

Random I/O various arrays (version: 0)

Comparing performance of: mixed use array vs single use array vs typed array

Created: 5 years ago by: Registered User

Jump to the latest result

mixed use array

single use array

typed array

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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