If it captures variables, it is not possible to manually declare the type. You can however hide it in an std::function. But then you probably get some overhead and some heap allocations in real life.
Well, nobody's forced it, but my company publishes content on TikTok that drives customers, and I want to be able to see it myself. You'd be surprised how many CISOs and security workers are on TikTok.
What kind of 2FA? I run OTP on my work laptop. Yes, it's maybe not really a 2nd factor if someone had access to my laptop with LUKS open. But at least I don't expect any automated attack because it's my own piece of code using an otp library.
Um... no. This is 100% completely and totally wrong.
x86-64 requires the hardware to support SSE2, which has native single-precision and double-precision instructions for floating-point (e.g., scalar multiply is MULSS and MULSD, respectively). Both the single precision and the double precision instructions will take the same time, except for DIVSS/DIVSD, where the 32-bit float version is slightly faster (about 2 cycles latency faster, and reciprocal throughput of 3 versus 5 per Agner's tables).
You might be thinking of x87 floating-point units, where all arithmetic is done internally using 80-bit floating-point types. But all x86 chips in like the last 20 years have had SSE units--which are faster anyways. Even in the days when it was the major floating-point units, it wasn't any slower, since all floating-point operations took the same time independent of format. It might be slower if you insisted that code compilation strictly follow IEEE 754 rules, but the solution everybody did was to not do that and that's why things like Java's strictfp or C's FLT_EVAL_METHOD were born. Even in that case, however, 32-bit floats would likely be faster than 64-bit for the simple fact that 32-bit floats can safely be emulated in 80-bit without fear of double rounding but 64-bit floats cannot.
I agree with you. It should take the same time when thinking more about it. I remember learning this in ~2016 and I did performance test on Skylake which confirmed (Windows VS2015). I think I remember that i only tested with addsd/addss. Definitely not x87. But as always, if the result can not be reproduced... I stand corrected until then.
I tried to reproduce it on Ivybridge (Windows VS20122) and failed (mulss and muldd) [0]. single and double precision takes the same time. I also found a behavior where the first batch of iterations takes more time regardless of precision. It is possible that this tricked me last time.
Sure, I clarified this in a sibling comment, but I kind of meant that I will use the slower "money" or "decimal" types by default. Usually those are more accurate and less error-prone, and then if it actually matters I might go back to a floating point or integer-based solution.
I think this is only true if using x87 floating point, which anything computationally intensive is generally avoiding these days in favor of SSE/AVX floats. In the latter case, for a given vector width, the cpu can process twice as many 32 bit floats as 64 bit floats per clock cycle.
Yes, as I wrote, it is only true for one float value.
SIMD/MIMD will benefit of working on smaller width. This is not only true because they do more work per clock but because memory is slow. Super slow compared to the cpu. Optimization is alot about cache misses optimization.
(But remember that the cache line is 64 bytes, so reading a single value smaller than that will take the same time. So it does not matter in theory when comparing one f32 against one f64)
I think you mean the LGPL? It allows you to "convey a combined work under terms of your choice" as long as the LGPL-covered part can be modified, which can be achieved either via dynamic linking or by providing the proprietary code as bare object files to relink statically. The GPL doesn't have this exception.
First IANACC (I'm not a compiler programmer), but this is my understanding:
What do you mean by interface?
A dynamic library is handled very different from a static one. A dynamic library is loaded into the process virtual memory address space. There will be a tree trace there of loaded libraries. (I would guess this program walks this tree. But there may be better ways i do not know of that this program utilize)
In the world of gnu/linux a static library is more or less a collection of object files. The linker, to my best knowledge, will not treat the content of the static libraries different than from your own code. LTO can take place.
In the final elf the static library will be indistinguishable from your own code.
My experience of the symbole table in elf files is limited and I do not know if they could help to unwrap static library dependencies. (A debug symbol table would of course help).
I know this is maybe not the answer you want, but if you are just interested in getting the job done there exist companies that are experts on this, for example:
The first thing that is required is to define what they are trying to do. In other words, list some question and answer examples. It's amazing how many people are unwilling or unable to do this and just jump to "we need to train a custom model". To do what exactly, or answer what kinds of questions? I have actually had multiple clients refuse to do that.
