OPTIMIZING THE JAVA VIRTUAL MACHINE INSTRUCTION SET BY ...

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phone numbers before the add, delete, find and sort operations are performed.
213 javac: Generates Java class files from Java source code using the
Java compiler from Sun’s Java Development Kit version 1.0.2.
222 mpegaudio: This application decompresses MPEG Layer-3 audio
files. A code obfuscater was used on the class files that make up the
application.
227 mtrt: Uses ray tracing to generate a scene depicting a dinosaur.
Two threads of execution run in parallel, each rendering the scene.
228 jack: This tool is an automatic compiler parser generator which
generates itself several times. The benchmark is an early version [79] of
the application now known as JavaCC [8].
4.2.3 Kaffe Performance
When this study was begun it was assumed that the Kaffe virtual machine would
show the greatest performance loss as a result of despecialization. This expectation
was based on the fact that the Kaffe interpreter does not perform any advanced optimizations.
As a result, there was no possibility that the extra work introduced
by performing despecialization would subsequently be removed during an optimization
process. It was expected that there would be a particularly large increase in
application runtime when widening and non-integer constant despecializations were
performed. For widening despecializations, this expectation was based on the fact
that the process of loading a value from the constant pool is considerably more involved
than the process of decoding the arguments to a bipush or sipush bytecode.
Similarly, loading a value from the constant pool is much more expensive than placing
a non-integer constant value directly onto the operand stack, leading to this expectation
for non-integer constant despecialization. It was also expected that branch
despecializations that result in an additional iconst 0 or swap bytecode being introduced
would be harmful to application performance because an extra iteration of the
fetch-decode-execute process must be performed to handle the additional bytecode.
The results of testing the despecialization conditions outlined previously in Table
4.6 are summarized in Table 4.7. It shows the total change in performance across
all 7 benchmarks tested when compared to the baseline execution time. This value