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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:
6 years ago
by:
Guest
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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>
Run tests (4)
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Test case name
Result
Math.random()
crypto.getRandomValues()
crypto.getRandomValues() UINT
crypto.getRandomValues() UINT8
Fastest:
N/A
Slowest:
N/A
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Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
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:
repeated Math.random() vs crypto.getRandomValues()
Math.random vs crypto.getRandom Alberto
Math.random vs Crypto.getRandomValues for 10k values
crypto.getRandomValues vs Math.random()
Math.floor(Math.random()) vs crypto.getRandom
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