Benchmark: array vs float64 for io and slice

Script Preparation code:

function getRandomInt(max) {
  return Math.floor(Math.random() * Math.floor(max));
}
var a = [...Array(10000)].map(_ => Math.random(1000000));
var ta = (new Float64Array(10000)).map(_ => Math.random(1000000));

AخA
 
function getRandomInt(max) {  return Math.floor(Math.random() * Math.floor(max));}var a = [...Array(10000)].map(_ => Math.random(1000000));var ta = (new Float64Array(10000)).map(_ => Math.random(1000000));

Tests:

array slice
a.slice(0);
a.slice(0);
typedArray slice
ta.slice(0);
ta.slice(0);

array i/o

for (let i = 0; i < 10000; ++i) {
  a[i] = a[i] + 1;
}

 
for (let i = 0; i < 10000; ++i) {  a[i] = a[i] + 1;}

typedArray i/o

for (let i = 0; i < 10000; ++i) {
  ta[i] = ta[i] + 1;
}
let tb = Array.from(ta);

 
for (let i = 0; i < 10000; ++i) {  ta[i] = ta[i] + 1;}let tb = Array.from(ta);

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
array slice
typedArray slice
array i/o
typedArray i/o

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:132.0) Gecko/20100101 Firefox/132.0

Browser/OS: Firefox 132 on Windows

View result in a separate tab

Test name	Executions per second
array slice	34233.9 Ops/sec
typedArray slice	42052.5 Ops/sec
array i/o	119236.4 Ops/sec
typedArray i/o	10578.4 Ops/sec

Autogenerated LLM Summary (model llama3.2:3b, generated 4 months ago):

I'd be happy to explain the benchmark being tested on MeasureThat.net.

Benchmark Definition The benchmark is designed to compare the performance of JavaScript arrays and TypedArrays (Float64Arrays) in various operations, specifically slicing and modifying elements.

Test Cases

There are four test cases:

array slice: Measures the time it takes to execute the a.slice(0) operation.
typedArray slice: Measures the time it takes to execute the ta.slice(0) operation.
array i/o: Measures the time it takes to modify elements in an array using a loop (for (let i = 0; i < 10000; ++i) { a[i] = a[i] + 1; }).
typedArray i/o: Measures the time it takes to convert a Float64Array to an Array and then modify elements in the resulting array (for (let i = 0; i < 10000; ++i) { ta[i] = ta[i] + 1; } let tb = Array.from(ta);).

Comparison of Options

In each test case, two options are compared:

Array: The built-in JavaScript array type.
TypedArray (Float64Array): A typed array that represents a sequence of 64-bit floating-point numbers.

Pros and Cons

Here's a brief summary of the pros and cons of each option:

array slice:
- Pros: Fast, widely supported, easy to use.
- Cons: May have performance issues for very large datasets or complex operations.
typedArray slice:
- Pros: Can provide better performance for certain types of data (e.g., floating-point numbers) and may be more memory-efficient.
- Cons: Less common usage, may require additional setup and configuration.
array i/o:
- Pros: Fast, widely supported, easy to use.
- Cons: May have performance issues for very large datasets or complex operations.
typedArray i/o:
- Pros: Can provide better performance for certain types of data (e.g., floating-point numbers) and may be more memory-efficient.
- Cons: Requires additional setup (converting to an Array), and the conversion process can introduce overhead.

Other Considerations

When choosing between arrays and TypedArrays, consider the following factors:

Data type: If you're working with floating-point numbers or other specialized data types, a TypedArray may be more suitable.
Performance: If you need optimized performance for large datasets or complex operations, consider using a TypedArray.
Memory efficiency: If memory is a concern, a TypedArray may be more efficient due to its ability to represent specific data types.

Library and Special JS Features

In the benchmark code, the following libraries are used:

Float64Array: A typed array that represents a sequence of 64-bit floating-point numbers. This library is built-in to JavaScript.
Array.from(): A method that converts an iterable object into an Array. This method is part of the modern JavaScript API.

No special JS features or syntax are used in this benchmark.

Alternatives

If you're looking for alternatives to MeasureThat.net, consider the following options:

Benchmarking libraries: Libraries like Benchmark.js, Fast.js, or Microbenchmark allow you to write custom benchmarks and run them on different platforms.
WebAssembly: WebAssembly provides a platform-agnostic way to execute optimized code in the browser, which can be useful for benchmarking performance-critical code.

Keep in mind that these alternatives may require more setup and configuration than MeasureThat.net.

LLMs can make mistakes. Check important info.

I'd be happy to explain the benchmark being tested on MeasureThat.net.

**Benchmark Definition**
The benchmark is designed to compare the performance of JavaScript arrays and TypedArrays (Float64Arrays) in various operations, specifically slicing and modifying elements.

**Test Cases**

There are four test cases:

1. `array slice`: Measures the time it takes to execute the `a.slice(0)` operation.
2. `typedArray slice`: Measures the time it takes to execute the `ta.slice(0)` operation.
3. `array i/o`: Measures the time it takes to modify elements in an array using a loop (`for (let i = 0; i < 10000; ++i) { a[i] = a[i] + 1; }`).
4. `typedArray i/o`: Measures the time it takes to convert a Float64Array to an Array and then modify elements in the resulting array (`for (let i = 0; i < 10000; ++i) { ta[i] = ta[i] + 1; } let tb = Array.from(ta);`).

**Comparison of Options**

In each test case, two options are compared:

* **Array**: The built-in JavaScript array type.
* **TypedArray (Float64Array)**: A typed array that represents a sequence of 64-bit floating-point numbers.

**Pros and Cons**

Here's a brief summary of the pros and cons of each option:

1. `array slice`:
	* Pros: Fast, widely supported, easy to use.
	* Cons: May have performance issues for very large datasets or complex operations.
2. `typedArray slice`:
	* Pros: Can provide better performance for certain types of data (e.g., floating-point numbers) and may be more memory-efficient.
	* Cons: Less common usage, may require additional setup and configuration.
3. `array i/o`:
	* Pros: Fast, widely supported, easy to use.
	* Cons: May have performance issues for very large datasets or complex operations.
4. `typedArray i/o`:
	* Pros: Can provide better performance for certain types of data (e.g., floating-point numbers) and may be more memory-efficient.
	* Cons: Requires additional setup (converting to an Array), and the conversion process can introduce overhead.

**Other Considerations**

When choosing between arrays and TypedArrays, consider the following factors:

* **Data type**: If you're working with floating-point numbers or other specialized data types, a TypedArray may be more suitable.
* **Performance**: If you need optimized performance for large datasets or complex operations, consider using a TypedArray.
* **Memory efficiency**: If memory is a concern, a TypedArray may be more efficient due to its ability to represent specific data types.

**Library and Special JS Features**

In the benchmark code, the following libraries are used:

* `Float64Array`: A typed array that represents a sequence of 64-bit floating-point numbers. This library is built-in to JavaScript.
* `Array.from()`: A method that converts an iterable object into an Array. This method is part of the modern JavaScript API.

No special JS features or syntax are used in this benchmark.

**Alternatives**

If you're looking for alternatives to MeasureThat.net, consider the following options:

* **Benchmarking libraries**: Libraries like Benchmark.js, Fast.js, or Microbenchmark allow you to write custom benchmarks and run them on different platforms.
* **WebAssembly**: WebAssembly provides a platform-agnostic way to execute optimized code in the browser, which can be useful for benchmarking performance-critical code.

Keep in mind that these alternatives may require more setup and configuration than MeasureThat.net.

Related benchmarks:

array vs float64 for io and slice (version: 0)

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

Created: one year ago by: Guest

Jump to the latest result

array slice

typedArray slice