Benchmark: unbiased ranged random integer generation functions

Script Preparation code:

const ta16 = new Uint16Array(1);
const ta32 = new Uint32Array(1);
const bound = 13000;

Tests:

Classic 16
if ((bound & -bound) === bound) { window.crypto.getRandomValues(ta16); return bound * ta16[0] >>> 16; } const limit = 65536 - 65536 % bound; do { window.crypto.getRandomValues(ta16); } while (ta16[0] >= limit); return ta16[0] % bound;
Mul shf 16
if ((bound & -bound) === bound) { window.crypto.getRandomValues(ta16); return bound * ta16[0] >>> 16; } const limit = (-bound >>> 0) % bound; let value; do { window.crypto.getRandomValues(ta16); value = ta16[0] * bound; } while ((value & 65535) < limit); return value >>> 16;
Imul shf 16
if ((bound & -bound) === bound) { window.crypto.getRandomValues(ta16); return bound * ta16[0] >>> 16; } const limit = (-bound >>> 0) % bound; let value; do { window.crypto.getRandomValues(ta16); value = Math.imul(ta16[0], bound); } while ((value & 65535) < limit); return value >>> 16;
Classic int
if ((bound & -bound) === bound) { window.crypto.getRandomValues(ta32); return ta32[0] * bound / 4294967296 >>> 0; } const limit = 4294967296 - 4294967296 % bound; do { window.crypto.getRandomValues(ta32); } while (ta32[0] >= limit); return ta32[0] % bound;
Mul shf bigint
if ((bound & -bound) === bound) { window.crypto.getRandomValues(ta32); return ta32[0] * bound / 4294967296 >>> 0; } const limit = (-bound >>> 0) % bound; let bits, mLow; let mHigh; do { window.crypto.getRandomValues(ta32); bits = ta32[0] >>> 1; const m = BigInt(bits) * BigInt(bound); mLow = Number(m & 2147483647n); mHigh = Number(m >> 31n); } while (mLow < limit); return mHigh;
Mul shf 32
if ((bound & -bound) === bound) { window.crypto.getRandomValues(ta32); return ta32[0] * bound / 4294967296 >>> 0; } const limit = (-bound >>> 0) % bound; let value; do { window.crypto.getRandomValues(ta32); value = ta32[0] * bound; } while ((value & 4294967295) % bound < limit); return value / 4294967296 >>> 0;
java nextInt16(bound)
if ((bound & -bound) === bound) { crypto.getRandomValues(ta16); return bound * ta16[0] >>> 16; } let value; do { crypto.getRandomValues(ta16); value = ta16[0] % bound; } while (ta16[0] - value + (bound - 1) < 0); return value;
java nextInt32(bound)
if ((bound & -bound) === bound) { window.crypto.getRandomValues(ta32); return ta32[0] * bound / 4294967296 >>> 0; } let bits, value; do { window.crypto.getRandomValues(ta32); bits = ta32[0] >>> 1; value = bits % bound; } while (bits - value + (bound - 1) < 0); return value;

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Classic 16
Mul shf 16
Imul shf 16
Classic int
Mul shf bigint
Mul shf 32
java nextInt16(bound)
java nextInt32(bound)

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 10 months ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/137.0.0.0 Safari/537.36

Browser/OS: Chrome 137 on Windows

View result in a separate tab

Test name	Executions per second
Classic 16	3156994.5 Ops/sec
Mul shf 16	3150879.8 Ops/sec
Imul shf 16	3149800.8 Ops/sec
Classic int	3133589.8 Ops/sec
Mul shf bigint	2397238.2 Ops/sec
Mul shf 32	1395642.2 Ops/sec
java nextInt16(bound)	2981598.5 Ops/sec
java nextInt32(bound)	3113806.0 Ops/sec

Related benchmarks:

unbiased ranged random integer generation functions (version: 16)

Comparing performance of: Classic 16 vs Mul shf 16 vs Imul shf 16 vs Classic int vs Mul shf bigint vs Mul shf 32 vs java nextInt16(bound) vs java nextInt32(bound)

Created: 10 months ago by: Registered User

Jump to the latest result

Classic 16

Mul shf 16

Imul shf 16

Classic int

Mul shf bigint

Mul shf 32

java nextInt16(bound)

java nextInt32(bound)

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A