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\section{MLRISC Based Compiler}
A traditional compiler will typically consist of a
\begin{color}{#dd0000}lex/yacc\end{color} based front end, an
\begin{color}{#DD0000}optimization\end{color}
phase that is repeatedly invoked
over some intermediate representation, and finally a
\begin{color}{#DD0000}back end\end{color}
code generation phase. The intermediate
representation is usually at a level of detail appropriate to the
optimization being performed, and may be far removed from the
native instructions of the target architecture. The back end
proceeds by translating the intermediate representation into
instructions and registers for an abstract machine that is much
closer to the target architecture. Retargetting is then achieved
by mapping the registers and instructions of the abstract machine
to registers and instructions of the target architecture.
\br{clear=left}
\image{MLRISC based compiler}{pictures/png/compiler-2.png}{align=right}
An MLRISC based compiler, on the other hand, translates the
intermediate representation into MLRISC instructions and it is the
MLRISC instructions that get mapped onto instructions of the target
architecture. Another possibility is to translate the front end
abstract machine instructions instead of the intermediate
representation. Once MLRISC instructions have been generated,
nearly all aspects of high quality code generation come for free. A
long story would be cut short if MLRISC were just another abstract
machine.
\begin{color}{#580000} The key idea behind MLRISC is that there is no
single MLRISC instruction set or intermediate program
representation, \end{color} but the MLRISC intermediate representation
is specialized to the needs of the front end source language being
compiled. The specialization does not stop there, but the:
\begin{itemize}
\item \begin{color}{#005500}target instruction set\end{color},
\item \begin{color}{#005500}flowgraph\end{color}, and
\item \begin{color}{#005500}entire optimization suite\end{color}
\end{itemize}
are specialized to the needs of the front end. The ability to
consistently specialize each of these to create a back end for a
specific language, summarizes the characteristics of MLRISC that
distinguishes it from other retargetable backends.
\begin{color}{#580000} It is important to emphasize that little
optimizations performed on the MLRISC intermediate
representation. \end{color} Most optimizations are done on a flowgraph of
target machine instructions, to enable optimizations that take advantage
of the characteristics of each architectural.
The MLRISC intermediate representation is just used as a stepping
stone to get to the flowgraph.
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