Timeline for Is there a floating point CSPRNG?
Current License: CC BY-SA 3.0
7 events
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| Jul 23, 2018 at 1:10 | comment | added | axapaxa | Poly1305-float is slower on even SSE2-capable CPUs. IEEE 754 is surely widely used, but problems often arise. Just google "cpu gpu float results" or "Intermediate Floating-Point Precision". I also never said it can't be done. Now can we please put that debate to end? Thanks! | |
| Jul 10, 2018 at 21:47 | comment | added | Squeamish Ossifrage | Floating-point arithmetic is not hard to reproduce in diverse environments. IEEE 754 arithmetic is well-understood, widely implemented, and absolutely predictable and reproducible. Floating-point division by zero is no more a problem than integer division by zero, which is already not a problem any cipher designers worry about—actually, floating-point division by zero has more consistent semantics than integer division by zero, spelled out and consistently implemented for decades. Sometimes crypto is effectively implemented with floating-point arithmetic, like Poly1305. | |
| Jun 11, 2018 at 13:50 | comment | added | axapaxa | @ErikAronesty Of course they can be modeled as one another, using very complex routines (that are very slow). Of course entropy exists in one and second, but floats have less entropy (NaNs come to mind, those aren't correct values for FPU calculations). Making special-purpose FPU is hard, but is easily in reach of powerful adversary. Please if you have any more questions, ask new question. | |
| Jun 1, 2018 at 18:01 | comment | added | Erik Aronesty | Obviously any FP operation can be modeled as integer and vice versa, so claims to the existence of entropy in one or the other is odd at best. It would be very challenging to make a special-purpose FPU that beat a general purpose FPU.... unless the algorithm was poorly developed. | |
| May 1, 2017 at 21:32 | comment | added | axapaxa | @ErikAronesty you are mistaking things. ASICs will beat FPUs, since FPUs are all made of ASICs, so you can make more specialized ASICs to win with your general FPU. CSPRNG operations cannot usually be represented as FP operations, because of precision and defined modulus. Also you seem to mistake what entropy is, and that FP has defined precision and because of that entropy (which is actually more limited than in integer operations!). | |
| May 1, 2017 at 16:55 | comment | added | Erik Aronesty | FPGA is a non issue. ASICs are not going to beat FPUs at floating-point operations. As long as the ops are FP heavy, it should be OK. And since many CSPRNG's are integer analogs of chaotic formulae that can be represented as FP operations, using a true FP version should work well. My problem is that most algos capture only one bits of entropy per iteration... Maybe the best way to do this is to simple use SHA3 on a series of steps. | |
| Apr 25, 2017 at 21:50 | history | answered | axapaxa | CC BY-SA 3.0 |