Wtf is up with the clown car that is floating point standards?
I wasn't a big fan of floating point until I worked with a former college professor who had taught astrophysics. When possible, he preferred to use respected libraries that would give accurate results fast. But when he had to implement things himself, he didn't always necessarily want the fastest or the most accurate implementation; he'd intentionally make and document the tradeoffs for his implementation. He could analyze an algorithm to estimate the accumulated units in the last place error ( https://en.wikipedia.org/wiki/Unit_in_the_last_place ), but he realized when that wasn't necessary.
DEC64 is just some bullshit one dude made up, and has nothing to do with “floating-point standards.”
One of the most important things that IEEE 754 mandates is gradual underflow (denormals) in the smallest binate. Otherwise you have a giant non-monotonic jump between the smallest normalizable float and zero. Which plays havoc with the stability of numerical algorithms.
The problem you run into is that the compiler generally does not implement the IEEE 754 model fully strictly, especially under default flags--you have to opt into strict IEEE 754 conformance, and even there, I'd be wary of the potential for bugs. (Hence one of the things I'm working on, quite slowly, is a special custom compiler that is designed to have 100% predictable assembly output for floating-point operations so that I can test some floating-point implementation things without having to worry about pesky optimizations interfering with me).
[1] The biggest stumbling block is denormal support: a lot of processors opted to support denormals only by trapping on it and having an OS-level routine to fix up the output. That said, both AMD and Apple have figured out how to support denormals in hardware with no performance penalty (Intel has some way to go), and from what I can tell, even most GPUs have given up and added full denormal support as well.