Benchmark: crypto.getRandomValues(new Uint8Array(4)) vs crypto.getRandomValues(new Uint16Array(2)) vs crypto.getRandomValues(new Uint32Array(1))

Tests:

crypto.getRandomValues(new Uint8Array(4))
crypto.getRandomValues(new Uint8Array(4))
crypto.getRandomValues(new Uint16Array(2))
crypto.getRandomValues(new Uint16Array(2))
crypto.getRandomValues(new Uint32Array(1))
crypto.getRandomValues(new Uint32Array(1))

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
crypto.getRandomValues(new Uint8Array(4))
crypto.getRandomValues(new Uint16Array(2))
crypto.getRandomValues(new Uint32Array(1))

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/17.1.2 Safari/605.1.15

Browser/OS: Safari 17 on Mac OS X 10.15.7

View result in a separate tab

crypto.getRandomValues(new Uint8Array(4))

3.1M/s

crypto.getRandomValues(new Uint32Array(1))

3.1M/s

crypto.getRandomValues(new Uint16Array(2))

3.1M/s

View exact numbers

Test name	Executions per second
✓ crypto.getRandomValues(new Uint8Array(4))	3,095,116 Ops/sec
crypto.getRandomValues(new Uint32Array(1))	3,083,364 Ops/sec
crypto.getRandomValues(new Uint16Array(2))	3,081,946 Ops/sec

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

LLMs can make mistakes. Check important info.

**Overview of the Benchmark**

The provided benchmark, hosted on MeasureThat.net, compares the performance of three different approaches for generating random values using the `crypto.getRandomValues()` method in JavaScript.

**Test Cases and Options Compared**

The test cases compare the execution time of `crypto.getRandomValues()` with three different array types:

1. `Uint8Array(4)`: an array of 4 unsigned 8-bit integers
2. `Uint16Array(2)`: an array of 2 unsigned 16-bit integers
3. `Uint32Array(1)`: an array of 1 unsigned 32-bit integer

These test cases aim to determine which approach provides the fastest execution time.

**Pros and Cons of Each Approach**

1. **`Uint8Array(4)`**: This approach is likely to be the fastest since it requires the fewest bytes to store and generate random values.
	* Pros: Minimal memory allocation, fast data generation
	* Cons: Limited range (0-255) for generating random numbers
2. **`Uint16Array(2)`**: This approach provides a larger range than `Uint8Array(4)` but still requires relatively few bytes to store and generate random values.
	* Pros: Larger range (0-65535) for generating random numbers, moderate performance
	* Cons: Still limited memory allocation, not as fast as `Uint8Array(4)`
3. **`Uint32Array(1)`**: This approach requires the most bytes to store and generate random values, making it likely to be the slowest.
	* Pros: Largest range (0-4294967295) for generating random numbers
	* Cons: Most memory allocation, slow data generation

**Library Used: `crypto`**

The `crypto` library is a built-in JavaScript module that provides cryptographic functions, including the `getRandomValues()` method. This method generates random values based on the provided array type.

**Special JS Feature/Syntax (None)**

There are no special JavaScript features or syntax used in this benchmark.

**Other Considerations**

* The test cases use a desktop browser (Safari 17) to ensure consistent results.
* The `ExecutionsPerSecond` metric is reported for each test case, indicating the number of random values generated per second.

**Alternatives**

For those interested in exploring alternative approaches or testing other cryptographic functions, some possible alternatives include:

1. Using a dedicated library like Web Cryptography API (W3C) or crypto-jelly
2. Implementing custom random number generators using algorithms like Linear Congruential Generator (LCG)
3. Testing other cryptographic functions, such as `crypto.subtle.generateKey()` or `crypto.subtle.importKey()`

These alternatives may provide different trade-offs in terms of performance, security, and usability, making them suitable for specific use cases or requirements.

crypto.getRandomValues(new Uint8Array(4)) vs crypto.getRandomValues(new Uint16Array(2)) vs crypto.getRandomValues(new Uint32Array(1)) (version: 0)

Comparing performance of: `crypto.getRandomValues(new Uint8Array(4)) vs crypto.getRandomValues(new Uint16Array(2)) vs crypto.getRandomValues(new Uint32Array(1))`

Created: 2 years ago by: Guest

Go to the latest result

crypto.getRandomValues(new Uint8Array(4))

crypto.getRandomValues(new Uint16Array(2))

crypto.getRandomValues(new Uint32Array(1))

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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

crypto.getRandomValues(new Uint8Array(4)) vs crypto.getRandomValues(new Uint16Array(2)) vs crypto.getRandomValues(new Uint32Array(1)) (version: 0)

Comparing performance of: crypto.getRandomValues(new Uint8Array(4)) vs crypto.getRandomValues(new Uint16Array(2)) vs crypto.getRandomValues(new Uint32Array(1))

Created: 2 years ago by: Guest

Go to the latest result

crypto.getRandomValues(new Uint8Array(4))

crypto.getRandomValues(new Uint16Array(2))

crypto.getRandomValues(new Uint32Array(1))

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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

Related benchmarks

Comparing performance of: `crypto.getRandomValues(new Uint8Array(4)) vs crypto.getRandomValues(new Uint16Array(2)) vs crypto.getRandomValues(new Uint32Array(1))`