Benchmark: array vs Float64Array vs Float32Array

Script Preparation code:

var a = [...Array(10000)].map(_ => Math.random());
var ta = (new Float64Array(10000)).map(_ => Math.random());
var tb = (new Float32Array(10000)).map(_ => Math.random());

Tests:

array reverse
a.reverse();
Float64Array reverse
ta.reverse();
array i/o
for (let i = 0; i < 10000; ++i) a[i] = a[i] + 1;
Float64Array i/o
for (let i = 0; i < 10000; ++i) ta[i] = ta[i] + 1;
Float32Array reverse
tb.reverse();
Float32Array i/o
for (let i = 0; i < 10000; ++i) tb[i] = tb[i] + 1;

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
array reverse
Float64Array reverse
array i/o
Float64Array i/o
Float32Array reverse
Float32Array i/o

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/148.0.0.0 Safari/537.36

Browser/OS: Chrome 148 on Windows

View result in a separate tab

Test name	Executions per second
array reverse	137744.2 Ops/sec
Float64Array reverse	384684.7 Ops/sec
array i/o	50165.1 Ops/sec
Float64Array i/o	37166.0 Ops/sec
Float32Array reverse	394459.0 Ops/sec
Float32Array i/o	35437.4 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 JSON and explain what's being tested, compared, and the pros/cons of different approaches.

**Benchmark Definition**

The benchmark definition represents a JavaScript function or operation that will be executed multiple times to measure its performance. In this case, there are six test cases:

1. `array.reverse();`
2. `Float64Array.reverse();`
3. `for (let i = 0; i < 10000; ++i) a[i] = a[i] + 1;` (input/output operation on an array)
4. `for (let i = 0; i < 10000; ++i) ta[i] = ta[i] + 1;` (input/output operation on a Float64Array)
5. `tb.reverse();`
6. `for (let i = 0; i < 10000; ++i) tb[i] = tb[i] + 1;` (input/output operation on a Float32Array)

**Library and Features**

Some test cases use libraries or special JavaScript features:

* Test case 4 (`ta` array) uses `Float64Array`, which is a typed array that can store 64-bit floating-point numbers.
* Test case 6 (`tb` array) uses `Float32Array`, which is a typed array that can store 32-bit floating-point numbers.

There are no special JavaScript features or syntax used in this benchmark, such as async/await, Promises, or Web Workers.

**Approaches Compared**

The benchmark compares different approaches for the following operations:

1. Reversing an array or a typed array (Float64Array or Float32Array)
2. Performing input/output operations on arrays and typed arrays

**Pros and Cons of Different Approaches**

Here's a brief overview of the pros and cons of each approach:

1. **Reversing an array or a typed array:**
	* Using `reverse()` method:
		+ Pros: simple, widely supported, and efficient for small to medium-sized datasets.
		+ Cons: can be slow for very large datasets due to its iterative nature.
	* Using `for` loop with indexing:
		+ Pros: can be faster than the `reverse()` method for very large datasets, as it only accesses elements once.
		+ Cons: requires manual memory management and is more error-prone.
2. **Performing input/output operations on arrays and typed arrays:**
	* Using a `for` loop with indexing:
		+ Pros: allows direct access to array elements, making it suitable for performance-critical code.
		+ Cons: requires manual memory management, which can lead to bugs.

**Other Alternatives**

If you're looking for alternatives or similar benchmarks, here are some examples:

* Micro-benchmarking platforms like ` benchmark.js`, ` jsbench`, or `jsperf` offer similar functionality and features.
* Google's `jsperf` is a popular benchmarking platform specifically designed for JavaScript performance testing.

Keep in mind that the specific use case and requirements of your project will influence the choice of benchmarking tool or approach.

Related benchmarks:

array vs Float64Array vs Float32Array (version: 0)

Comparing performance of: array reverse vs Float64Array reverse vs array i/o vs Float64Array i/o vs Float32Array reverse vs Float32Array i/o

Created: 5 years ago by: Guest

Jump to the latest result

array reverse

Float64Array reverse

array i/o

Float64Array i/o

Float32Array reverse

Float32Array i/o

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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