Benchmark: Math.random vs crypto.getRandom sizes

Tests:

Math.random()
Math.random()
crypto.getRandomValues()
crypto.getRandomValues(new Uint32Array(1))[0] / 4294967296
crypto.getRandomValues() UINT
crypto.getRandomValues(new Int32Array(1))[0] / 4294967296
crypto.getRandomValues() UINT8
crypto.getRandomValues(new Uint8Array(1))[0] / 4294967296

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Math.random()
crypto.getRandomValues()
crypto.getRandomValues() UINT
crypto.getRandomValues() UINT8

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 2 years ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:100.0) Gecko/20100101 Firefox/100.0

Browser/OS: Firefox 100 on Windows

View result in a separate tab

Test name	Executions per second
Math.random()	1300461952.0 Ops/sec
crypto.getRandomValues()	1605036.5 Ops/sec
crypto.getRandomValues() UINT	1590307.4 Ops/sec
crypto.getRandomValues() UINT8	1916413.1 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark definition and test cases.

**What is tested?**

The test cases measure the performance of three different methods to generate random numbers in JavaScript:

1. `Math.random()` - a built-in function that generates a random float number between 0 (inclusive) and 1 (exclusive).
2. `crypto.getRandomValues(new Uint32Array(1))[0] / 4294967296` - uses the Web Cryptography API to generate a cryptographically secure random integer.
3. `crypto.getRandomValues(new Int32Array(1))[0] / 4294967296` and `crypto.getRandomValues(new Uint8Array(1))[0] / 4294967296` - similar to the previous one, but uses different data types (int32 and uint8) for generating random integers.

**Options compared**

The three options are compared in terms of their performance, measured by the number of executions per second. The option with the highest value is considered to be the fastest.

**Pros and cons of each approach:**

1. `Math.random()`:
	* Pros: simple, widely supported, no additional dependencies required.
	* Cons: not suitable for generating cryptographically secure random numbers, can produce predictable sequences in certain cases.
2. `crypto.getRandomValues()` (uint32):
	* Pros: provides a high level of randomness and predictability, suitable for cryptographic purposes.
	* Cons: requires the Web Cryptography API, which may not be supported by all browsers or devices.
3. `crypto.getRandomValues()` (int32) and `crypto.getRandomValues()` (uint8):
	* Pros: provide a good balance between randomness and performance.
	* Cons: similar to the previous one, require the Web Cryptography API.

**Library usage**

The `crypto` library is used in all three test cases. It provides a way to generate cryptographically secure random numbers using the Web Cryptography API. The `getRandomValues()` method returns an array of random values of a specified type (uint32, int32, or uint8), which are then scaled down by dividing by 4294967296 to produce a float value between 0 and 1.

**Special JavaScript features**

The test cases use the following special JavaScript feature:

* The `Uint8Array` and `Int32Array` constructors, which allow for creating arrays of specific data types.
* The `getRandomValues()` method, which is part of the Web Cryptography API.

If not mentioned earlier, no other special JavaScript features are used in these test cases.

**Alternative approaches**

Other alternatives to generate random numbers include:

1. Using a random number generator library or framework, such as Mathjs or Random.org.
2. Using a pseudo-random number generator algorithm, such as Linear Congruential Generator (LCG).
3. Using a cryptographically secure pseudorandom number generator, such as Fortuna PRNG.

However, the Web Cryptography API is considered a standard for generating cryptographically secure random numbers in modern browsers, making it a widely supported and recommended approach.

Related benchmarks:

Math.random vs crypto.getRandom sizes (version: 0)

Comparing performance of: Math.random() vs crypto.getRandomValues() vs crypto.getRandomValues() UINT vs crypto.getRandomValues() UINT8

Created: 4 years ago by: Guest

Jump to the latest result

Math.random()

crypto.getRandomValues()

crypto.getRandomValues() UINT

crypto.getRandomValues() UINT8

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):