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docs/HistoricalNotes/2001-04-16-DynamicCompilation.txt
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By Chris: By Chris:
LLVM has been designed with two primary goals in mind. First we strive to enable the best possible division of labor between static and dynamic compilers, and second, we need a flexible and powerful interface between these two complementary stages of compilation. We feel that providing a solution to these two goals will yield an excellent solution to the performance problem faced by modern architectures and programming languages. LLVM has been designed with two primary goals in mind. First we strive to
enable the best possible division of labor between static and dynamic
compilers, and second, we need a flexible and powerful interface
between these two complementary stages of compilation. We feel that
providing a solution to these two goals will yield an excellent solution
to the performance problem faced by modern architectures and programming
languages.
A key insight into current compiler and runtime systems is that a compiler may fall in anywhere in a "continuum of compilation" to do its job. On one side, scripting languages statically compile nothing and dynamically compile (or equivalently, interpret) everything. On the far other side, traditional static compilers process everything statically and nothing dynamically. These approaches have typically been seen as a tradeoff between performance and portability. On a deeper level, however, there are two reasons that optimal system performance may be obtained by a system somewhere in between these two extremes: Dynamic application behavior and social constraints. A key insight into current compiler and runtime systems is that a
compiler may fall in anywhere in a "continuum of compilation" to do its
job. On one side, scripting languages statically compile nothing and
dynamically compile (or equivalently, interpret) everything. On the far
other side, traditional static compilers process everything statically and
nothing dynamically. These approaches have typically been seen as a
tradeoff between performance and portability. On a deeper level, however,
there are two reasons that optimal system performance may be obtained by a
system somewhere in between these two extremes: Dynamic application
behavior and social constraints.
From a technical perspective, pure static compilation cannot ever give optimal performance in all cases, because applications have varying dynamic behavior that the static compiler cannot take into consideration. Even compilers that support profile guided optimization generate poor code in the real world, because using such optimization tunes that application to one particular usage pattern, whereas real programs (as opposed to benchmarks) often have several different usage patterns. From a technical perspective, pure static compilation cannot ever give
optimal performance in all cases, because applications have varying dynamic
behavior that the static compiler cannot take into consideration. Even
compilers that support profile guided optimization generate poor code in
the real world, because using such optimization tunes that application
to one particular usage pattern, whereas real programs (as opposed to
benchmarks) often have several different usage patterns.
On a social level, static compilation is a very shortsighted solution to the performance problem. Instruction set architectures (ISAs) continuously evolve, and each implementation of an ISA (a processor) must choose a set of tradeoffs that make sense in the market context that it is designed for. With every new processor introduced, the vendor faces two fundamental problems: First, there is a lag time between when a processor is introduced to when compilers generate quality code for the architecture. Secondly, even when compilers catch up to the new architecture there is often a large body of legacy code that was compiled for previous generations and will not or can not be upgraded. Thus a large percentage of code running on a processor may be compiled quite sub-optimally for the current characteristics of the dynamic execution environment. On a social level, static compilation is a very shortsighted solution to
the performance problem. Instruction set architectures (ISAs) continuously
For these reasons, LLVM has been designed from the beginning as a long-term solution to these problems. Its design allows the large body of platform independent, static, program optimizations currently in compilers to be reused unchanged in their current form. It also provides important static type information to enable powerful dynamic and link time optimizations to be performed quickly and efficiently. This combination enables an increase in effective system performance for real world environments. evolve, and each implementation of an ISA (a processor) must choose a set
of tradeoffs that make sense in the market context that it is designed for.
With every new processor introduced, the vendor faces two fundamental
problems: First, there is a lag time between when a processor is introduced
to when compilers generate quality code for the architecture. Secondly,
even when compilers catch up to the new architecture there is often a large
body of legacy code that was compiled for previous generations and will
not or can not be upgraded. Thus a large percentage of code running on a
processor may be compiled quite sub-optimally for the current
characteristics of the dynamic execution environment.
For these reasons, LLVM has been designed from the beginning as a long-term
solution to these problems. Its design allows the large body of platform
independent, static, program optimizations currently in compilers to be
reused unchanged in their current form. It also provides important static
type information to enable powerful dynamic and link time optimizations
to be performed quickly and efficiently. This combination enables an
increase in effective system performance for real world environments.