OPTIMIZING THE JAVA VIRTUAL MACHINE INSTRUCTION SET BY ...

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performing multicode substitution in the presence of 50 despecializations allowed more
bytecode dispatches to be removed for all of the benchmarks considered except for
201 compress. The 201 compress benchmark performed approximately 0.2 percent
more bytecode dispatches in the presence of 50 despecializations than when multicode
substitution was performed alone. In contrast, performing 50 despecializations
removed 16 percent more bytecode dispatch operations for 222 mpegaudio than performing
multicode substitution alone. The number of bytecode dispatch operations
removed by performing multicode substitution in the presence of 50 despecializations
was 4.4 percent larger for 213 javac and 8.3 percent larger for 228 jack. Only a
very small change in the number of transfers of control was observed for 202 jess
and 209 db.
8.5 Conclusion
This chapter combined the concepts of despecialization and multicode substitution
which were explored in previous chapters. The processes were combined by performing
a set of despecializations, profiling the applications in their despecialized form and
then identifying multicodes from the despecialized profile data.
When multicode substitution was performed in conjunction with 67 despecializations,
a performance loss of approximately 4 percent was observed compared to the
performance achieved when multicode substitution was performed alone. A portion of
the performance loss resulted due to the increased cost associated with executing the
despecialized form of the code stream. It was also observed that for some benchmarks,
performing despecialization decreased the effectiveness of multicode substitution at
reducing the number of transfers of control. This difference also contributed to the
observed performance loss.
A second set of despecializations was also considered in conjunction with multicode
substitution. In this set, 50 bytecodes were despecialized. Those specialized bytecodes
that previously demonstrated the greatest likelihood to increase application runtime
were left in their specialized form while the remaining specialized bytecodes were
replaced with their equivalent general purpose forms. Identifying multicodes in this
environment was shown to provide performance comparable to performing multicode
substitution in the absence of despecialization. Similar performance was achieved
because the despecializations performed were selected so as to minimize the negative
impact on application performance and because performing multicode selection under
these conditions resulted in fewer bytecode dispatches for some benchmarks.