OPTIMIZING THE JAVA VIRTUAL MACHINE INSTRUCTION SET BY ...

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10.2.6 Combining Multicodes and a JIT Compiler
The multicode work presented in Chapter 7 and Chapter 8 was conducted entirely
within the context of a Java interpreter. Many modern virtual machines make use
of a JIT compiler in order to improve application performance. Multicodes are very
well suited for use within an interpreter. Furthermore, the author believes that they
may also offer benefits when used in conjunction with a just-in-time compiler.
A JIT compiler converts Java bytecodes to platform specific machine language
instructions at runtime. The amount of time spent on this conversion process is
of great concern since the application’s user is waiting while the conversion process
takes place. Consequently, the thoroughness of the optimizations that are performed
is limited. Any optimization performed must achieve a performance gain after taking
into consideration the amount of time spent performing the optimization [11]. This
is not the case in a traditional optimizer which executes at compile time. In that
context, the only timing concern is that compile time remain reasonable, generally
allowing optimization algorithms to execute until an optimal result is achieved.
If multicodes were introduced into a virtual machine that makes use of a JIT
compiler then the need to perform runtime optimizations would be reduced. Since
the multicodes are determined ahead of time, representing a sequence of several bytecodes,
optimal machine language code can be determined for that sequence ahead of
time as well. Thus, when JIT compilation is performed, optimal machine language
code can be generated for the multicode without requiring any additional optimization
within it. Optimizations will still need to be performed for those portions of
the applications which do not make extensive use of multicodes and to handle the
boundaries between the multicodes. However, these runtime optimizations will be less
critical to the performance of the application because optimal machine language code
has already been generated for the multicodes which account for a large proportion
of the application’s execution.
The benefits multicodes have to a JIT compiler are similar to the benefits afforded
by bytecode idioms. However, unlike bytecode idioms, multicodes are identified from
profiling, ensuring that the sequences considered are actually executed with great
frequency. Multicode substitution also occurs ahead of time, eliminating the need to
perform the substitution when the class file is loaded. Both of these factors allow
longer candidate sequences to be considered. By determining multicodes through
profiling, a computer examines long sequences that are difficult for people to identify.
Performing the substitution ahead of time eliminates any concerns regarding the