OPTIMIZING THE JAVA VIRTUAL MACHINE INSTRUCTION SET BY ...

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Compared to the complete despecialization performed in Chapter 4, this table has
omitted 17 bytecodes. Five of these bytecodes are bipush, sipush, ldc, goto and
jsr. Each of these bytecodes is despecialized through a widening operation which
increases the number of bytes used to represent an operand accessed by the bytecode.
Examining the performance results from Chapter 4 revealed that performing widening
despecializations generally had a more harmful impact on application runtime
than most other despecialization categories. As a result, it was decided that these
bytecodes would not be despecialized.
The second category of despecializations identified in Chapter 4 that showed a
larger negative impact on application runtime was branch despecialization. These
despecializations also increase the total number of bytecodes executed because they replace
one specialized bytecode with two general purpose bytecodes. As a result, all of
the bytecodes in the branch despecialization category which included the if
bytecodes, if icmplt and if icmple were omitted from this list of despecializations.
Removing the widening and branch bytecodes from consideration left a total of
54 specialized bytecodes. Four additional bytecodes were omitted to bring the total
number of despecializations to 50. These bytecodes were aload 0, aload 1, iload 1
and iload 3. They were selected because the profiling work performed in Chapter
5 revealed that these were the four most frequently executed specialized bytecodes,
accounting for between 1.8 and 8.5 percent of the bytecodes executed by an application
on average.
Profiling was conducted in order to determine which sequences of bytecodes were
executed with greatest frequency once the 50 specialized bytecodes list in Table 8.1
were replaced with their equivalent general purpose forms. Multicodes were identified
from this profile data using the same techniques employed previously, comparing both
the transfer reduction and total bytecodes replaced scoring strategies for maximum
multicode lengths from 5 through 50. The performance of each of the six benchmarks
under consideration is shown in Figure 8.8 through Figure 8.13.
The performance results achieved by performing multicode substitution in the
presence of 50 despecializations are highly similar to the results achieved by performing
multicode substitution alone. The maximum improvement in performance
observed was 1.45 percent of the original runtime for 222 mpegaudio while the maximum
performance loss observed was 1.0 percent of the original runtime for 209 db.
The overall average change in performance across all six benchmarks was an improvement
of 0.2 percent of the original benchmark run times.
Analyzing the total number of transfers removed for each benchmark revealed that