The Difference Between RDRAND and RDSEED

Intel recently announced the addition of the RDSEED instruction to the Intel® 64 and IA-32 Architectures. An addition to Intel® Secure Key, this new instruction will appear in future generations of Intel processors.

Like RDRAND the RDSEED instruction returns random numbers, and with two instructions that appear to do the same thing it is only natural for the software developer to ask, "Which one should I use?" I'll provide both a short and long answer: the short answer is for developers who just want to know which instruction to use and when, and the long answer is for those who are interested in some of the theory behind the answer.

The short answer

The decision process for which instruction to use is mercifully simple, and based on what the output will be used for.

  • If you wish to seed another pseudorandom number generator (PRNG), use RDSEED
  • For all other purposes, use RDRAND

That's it. RDSEED is intended for seeding a software PRNG of arbitrary width. RDRAND is intended for applications that merely require high-quality random numbers.

The long answer

Both RDRAND and RDSEED return random numbers that are compliant to the U.S. National Institute of Standards and Technology (NIST) standards on random number generators.

Instruction Source

NIST Compliance

RDRAND Cryptographically secure pseudorandom number generator SP 800-90A
RDSEED Non-deterministic random bit generator SP 800-90B & C (drafts)

The numbers returned by RDSEED are referred to as "seed-grade entropy" and are the output of a true random number generator (TRNG), or an ehanced non-deterministic random number generator (ENRNG) in NIST-speak.  RDSEED is intended for use by software vendors who have an existing PRNG, but would like to benefit from the entropy source of Intel Secure Key. With RDSEED you can seed a PRNG of any size.

The numbers retuned by RDSEED have multiplicative prediction resistance. If you use two 64-bit samples with multiplicative prediction resistance to build a 128-bit value, you end up with a random number with 128 bits of prediction resistance (2128 * 2128 = 2256). Combine two of those 128-bit values together, and you get a 256-bit number with 256 bits of prediction resistance. You can continue in this fashion to build a random value of arbitrary width and the prediction resistance will always scale with it. Because its values have multiplicative prediction resistance RDSEED is intended for seeding other PRNGs.

In contrast, RDRAND is the output of a 128-bit PRNG that is compliant to NIST SP 800-90A. It is intended for applications that simply need high-quality random numbers. The numbers returned by RDRAND have additive prediction resistance because they are the output of a pseurandom number generator. If you put two 64-bit values with additive prediction resistance togehter, the prediction resistance of the resulting value is only 65 bits (264 + 264 = 265). To ensure that RDRAND values are fully prediction-resistant when combined together to build larger values you can follow the procedures in the DRNG Software Implementation Guide on generating seed values from RDRAND, but it's generally best and simplest to just use RDSEED for PRNG seeding.



Intel® Architecture Instruction Set Extensions Programming Reference

Intel® Digital Random Number Generator (DRNG) Software Implementation Guide

Para obtener información más completa sobre las optimizaciones del compilador, consulte nuestro Aviso de optimización.