Benchmark: array vs Float64Array (small)

Script Preparation code:

var a = [...Array(100)].map(_ => Math.random());
var ta = (new Float64Array(100)).map(_ => Math.random());

Tests:

array reverse
a.reverse();
typedArray reverse
ta.reverse();
array i/o
for (let i = 0; i < 100; ++i) a[i] = a[i] + 1;
typedArray i/o
for (let i = 0; i < 100; ++i) ta[i] = ta[i] + 1;

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
array reverse
typedArray reverse
array i/o
typedArray i/o

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

Let's dive into the world of JavaScript microbenchmarks!

**Benchmark Overview**

MeasureThat.net provides a platform for users to create and run JavaScript microbenchmarks. The benchmark you provided compares two approaches: arrays and TypedArrays (specifically, Float64Array) for small data sets.

**What is being tested?**

The test cases measure the performance of the following operations:

1. Reversing an array using `a.reverse()`
2. Performing input/output operations on an array (`a[i] = a[i] + 1`)
3. Reversing a TypedArray (Float64Array) using `ta.reverse()`
4. Performing input/output operations on a TypedArray (`ta[i] = ta[i] + 1`)

**Options compared**

Two options are being compared:

* **Arrays**: Using native JavaScript arrays (`a`)
* **TypedArrays**: Using typed arrays (`ta`), specifically Float64Array, which is similar to a regular array but provides more efficient memory management for floating-point numbers.

**Pros and Cons of each approach:**

* **Arrays**:
	+ Pros:
		- Wide support and compatibility across browsers and platforms
		- Easy to use and understand
	+ Cons:
		- Can be slower due to the overhead of dynamic typing and garbage collection
		- May not provide the same level of performance as typed arrays for numerical computations
* **TypedArrays**:
	+ Pros:
		- Provide more efficient memory management for numerical computations
		- Can lead to better performance, especially when working with large datasets or high-performance applications
	+ Cons:
		- Limited support and compatibility across browsers and platforms (although improving)
		- Requires a good understanding of the underlying data structures and may require additional setup

**Library/ Framework considerations**

None are mentioned in this benchmark.

**Special JS feature/syntax considerations**

No special features or syntax are used in these test cases. The focus is on comparing performance between two fundamental approaches to working with arrays: native JavaScript arrays and TypedArrays.

**Alternatives**

Other alternatives for numerical computations in JavaScript include:

* **BigInt**: Introduced in ECMAScript 2020, BigInt provides support for arbitrary-precision arithmetic and can be used instead of floating-point numbers for high-performance applications.
* **WebAssembly**: Provides a platform-independent way to execute compiled code on the web, which can offer significant performance advantages over traditional JavaScript execution.

Keep in mind that the choice of approach depends on the specific requirements and constraints of your project. For most use cases, arrays will suffice, but if you're working with high-performance numerical computations or need more control over memory management, TypedArrays or other alternatives might be a better fit.

Latest run results:

Run details: (Test run date: 3 years ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/94.0.4606.71 Safari/537.36

Browser/OS: Chrome 94 on Windows

View result in a separate tab

Test name	Executions per second
array reverse	6542864.5 Ops/sec
typedArray reverse	7424817.5 Ops/sec
array i/o	66043.4 Ops/sec
typedArray i/o	68038.9 Ops/sec

Related benchmarks:

array vs Float64Array (small) (version: 0)

Comparing performance of: array reverse vs typedArray reverse vs array i/o vs typedArray i/o

Created: 3 years ago by: Guest

Jump to the latest result

array reverse

typedArray reverse

array i/o

typedArray i/o

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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