Pytorch-Correlation-extension | Custom implementation of Corrleation Module | Machine Learning library

Is it possible to use a different gcc version inside a Conda environment?

Probably yes, except if you (or your Conda environment) needs or uses some GCC plugin. These plugins are specific to a particular version of GCC: a plugin coded for GCC 4.8 (such as my old GCC MELT) won't work with GCC 6. But see also this draft report on Bismon (which might become a successor to GCC MELT).

On Linux/x86-64, a C code compiled with GCC 4.8 would be compatible with the same code compiled with GCC 10, since both follow the same ABI and calling conventions.

For C++ code compiled with GCC, there could be subtle ABI or calling conventions incompatibilities (related to name mangling and exceptions).

Be also aware that Python 2 and Python 3 have different foreign function interfaces. Read chapters related to extending and embedding the Python interpreter.

See also the Program Library HowTo, Advanced Linux Programming and C++ dlopen mini-HowTo and Linux Assembly HowTo and of course Linux From Scratch.

On my system (Linux, remote server), gcc version is 4.8.5

You are allowed to compile and install a more recent GCC from its source code on your system. An installed GCC 4.8 can be use to build e.g. a GCC 8 from its source code (then installed into /usr/local/bin/gcc, then you just configure wisely your $PATH variable). You could even do that with the unsupported GCC 5.

On recent Debian or Ubuntu you would install dependencies with something like sudo aptitude build-dep g++ and you might also want to use Docker. You may need to download several gigabytes.

Some companies or freelancers are able (for a fee) to compile a GCC tailored for your system. I know AdaCore, but there are many others corporations or freelancers selling support on GCC. Contact me by email for more.

PS. On a powerful AMD Threadripper 2970WX desktop, I just built GCC 10.1 with make -j8 and g++ 9.3 on Debian/Sid in 10:21.38 elapsed time, requiring less than 7 Gbytes of disk space (for both GCC source code and object files). Of course, I disabled the compiler bootstrap. You could do the same thru ssh to your system (it could take an hour or two of elapsed time, because a Linux VPS has less cores so you might need to just make -j2).