Just-In-Time compilers are becoming increasingly popular for executing dynamic languages like Perl and Python and for semi-dynamic languages like Java and C#. Studies have shown that JIT techniques can get close to, and sometimes exceed, the performance of statically-compiled native code.
However, there is a problem with current JIT approaches. In almost every case, the JIT is specific to the object model, runtime support library, garbage collector, or bytecode peculiarities of a particular system. This inevitably leads to duplication of effort, where all of the good JIT work that has gone into one virtual machine cannot be reused in another.
JIT's are not only useful for implementing languages. They can also be used in other programming fields. Graphical applications can achieve greater performance if they can compile a special-purpose rendering routine on the fly, customized to the rendering task at hand, rather than using static routines. Needless to say, such applications have no need for object models, garbage collectors, or huge runtime class libraries.
Most of the work on a JIT is concerned with arithmetic, numeric type conversion, memory loads/stores, looping, performing data flow analysis, assigning registers, and generating the executable machine code. Only a very small proportion of the work is concerned with language specifics.
The goal of the
libjit project is to provide an extensive set of routines that takes care of the bulk of the JIT process, without tying the programmer down with language specifics. Where we provide support for common object models, we do so strictly in add-on libraries, not as part of the core code.