Programming Languages – Does Syntax Depend on Implementation?

While performance is really a result of implementation rather than languages, there are, in practice, faster and slower languages.

C is usually the fastest in comparisons. C compilers are relatively mature, and C programs require minimal run-time support. A C program will normally be compiled to something that can be loaded and executed, with just a little preparation on the part of the computer. (There have been C interpreters, and they were slow like you'd expect.)

Fortran is not usually in those computations, but is similar in most respects. Fortran was inherently faster in large-scale floating-point computations than the C of the original Standard, since the Fortran compiler could assume, say, that the three matrices passed to a multiplication program were disjoint, and could optimize on that basis. C compilers couldn't assume that.

Java programs are normally compiled to an artificial machine language, and that is normally compiled on the fly (just-in-time compiling). That could theoretically be faster than C-style compilation (it could make better guesses about the flow of execution, and it could tailor the compilation to the exact system in use), but in practice isn't. Java also requires more run-time support, such as a garbage collector, and the JIT compiler and runtime have to load and get going. That results in increased startup time, which can be noticeable.

Python programs are normally compiled to an artificial machine language and then interpreted, which is slower. It is possible to store the compiled files (".pyc"), but frequently only the source is stored, so to execute it is necessary to compile first and then interpret, which is slow. Also, Python has dynamic typing, which means the compiler doesn't know everything's type up front, and therefore Python functions have to be able to take different data types at runtime, which is inefficient.

There's always room for surprises. On one celebrated occasion, a CMU Common Lisp program out-number-crunched a Fortran program. Common Lisp requires garbage collection, which apparently wasn't an issue in that application, and normally is dynamically typed, but it's possible to declare all types statically. The Fortran compiler had a small inefficiency the CMU Common Lisp compiler didn't, and was duly improved afterwards.

It's important to remember that interpreting and compiling are not just alternatives to each other. In the end, any program that you write (including one compiled to machine code) gets interpreted. Interpreting code simply means taking a set of instructions and returning an answer.

Compiling, on the other hand, means converting a program in one language to another language. Usually it is assumed that when compilation takes place, the code is compiled to a "lower-level" language (eg. machine code, some kind of VM bytecode, etc.). This compiled code is still interpreted later on.

With regards to your question of whether there is a useful distinction between interpreted and compiled languages, my personal opinion is that everyone should have a basic understanding of what is happening to the code they write during interpretation. So, if their code is being JIT compiled, or bytecode-cached, etc., the programmer should at least have a basic understanding of what that means.