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Math.random() vs. random() v2
(version: 0)
Comparing performance of:
Math.random() vs random()
Created:
2 years ago
by:
Guest
Go to the latest result
Script Preparation code:
var random = (() => { const MAX = 2 ** 32 - 1; const pool = crypto.getRandomValues(new Uint32Array(1024)); // 4MB let index = 0; return () => { const value = pool[index]; index++; if (index === pool.length) { crypto.getRandomValues(pool); index = 0; } return value / MAX; }; })();
Tests:
Math.random()
Math.random()
random()
random()
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
Previous results
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Test case name
Result
Math.random()
random()
Fastest:
N/A
Slowest:
N/A
Latest run results:
Run details:
(Test run date:
one year ago
)
User agent:
Mozilla/5.0 (Windows NT 5.1; rv:52.0) Gecko/20100101 Firefox/52.0
Browser/OS:
Firefox 52 on Windows XP
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Embed Benchmark Result
<iframe src="https://measurethat.net/Embed?id=539198" width="100%" height="500px"></iframe>
Math.random()
185.7M/s
random()
10.6M/s
View exact numbers
Test name
Executions per second
✓
Math.random()
185,686,592 Ops/sec
random()
10,589,471 Ops/sec
Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
Let's break down the provided benchmark definition and test cases to understand what is being tested. **Benchmark Definition** The benchmark definition consists of two scripts: `Math.random()` and `random() v2`. The purpose of this benchmark is to compare the performance of these two functions in generating random numbers. **Options Compared** The options compared are: 1. **`Math.random()`**: This is a built-in JavaScript function that generates a random number between 0 (inclusive) and 1 (exclusive). 2. **`random() v2`**: This is a custom implementation of a random number generator, designed to be faster and more efficient than the native `Math.random()` function. **Pros and Cons** The pros and cons of these approaches are: * **`Math.random()`**: + Pros: Simple and easy to implement, widely supported across browsers and devices. + Cons: Can generate very low-quality random numbers (e.g., 0.5), which may not be suitable for certain applications (e.g., simulations, modeling). * **`random() v2`**: + Pros: Generates higher-quality random numbers, using a cryptographically secure pseudorandom number generator. + Cons: More complex to implement, requires additional setup and initialization. **Library Used** The `crypto.getRandomValues()` function is used in the custom implementation of `random() v2`. This function provides a way to generate cryptographically secure random numbers, which are suitable for applications that require high-quality randomness (e.g., simulations, encryption). **Special JS Feature or Syntax** There is no special JavaScript feature or syntax mentioned in this benchmark. However, it's worth noting that the custom implementation of `random() v2` uses a technique called "pooling" to generate random numbers, which is not a standard JavaScript feature. **Other Considerations** When comparing these two functions, it's essential to consider the following: * **Performance**: How fast does each function execute? * **Quality**: What kind of randomness do you need for your application (e.g., high-entropy, low-entropy)? * **Support**: Which browsers and devices support each function? **Other Alternatives** If you're looking for alternative approaches to generating random numbers in JavaScript, consider the following: 1. **`Math.random()` with a seed**: You can use `Math.random()` with a fixed seed to generate predictable random numbers. 2. **`crypto.randomUUID()`**: This function generates a cryptographically secure UUID, which can be used as a pseudo-random number generator. 3. **External libraries**: There are several external libraries available that provide high-quality random number generation, such as `random.org` or `seedrandom.js`. In conclusion, the benchmark compares the performance of two functions: `Math.random()` and a custom implementation called `random() v2`. The latter uses a cryptographically secure pseudorandom number generator to generate higher-quality random numbers.
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