OPTIMIZING THE JAVA VIRTUAL MACHINE INSTRUCTION SET BY ...

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However, while considering longer sequences may allow a larger number of bytecodes
to be replaced, or more transfers to be removed, there is also a potential cost associated
with selecting many long multicodes. Since a new codelet must be added to the
interpreter’s execution loop for each multicode selected, it is possible that choosing
many long multicodes may increase the size of the interpreter’s main loop beyond
the size of the instruction cache. Should this occur, it is likely that the performance
loss due to decreased cache utilization will outweigh the performance gain achieved
by multicode substitution.
7.6.1 Individual Benchmark Performance
Six benchmarks from the SPEC JVM98 benchmark suite were tested. These were
described previously in Section 4.2.2 as part of the discussion presented on despecialization.
The performance results achieved by performing multicode identification
and substitution for each benchmark are shown in Figure 7.10 through Figure 7.21.
Each of the following pages contains two graphs. The upper graph shows the
performance achieved for each combination of scoring system and maximum multicode
length considered. Fifty multicode substitutions were performed for each point shown
on the graph. For example, Figure 7.10 shows that, for the 201 compress benchmark,
application run time was reduced by approximately 18 percent when 50 multicodes
were identified using Total Bytecodes Replaced Scoring to identify multicodes of up
to 5 bytecodes in length. Similarly, Figure 7.10 shows that the best technique for
identifying multicodes for the 201 compress benchmark was to consider sequences up
to 35 bytecodes in length using Transfer Reduction scoring. Using this combination of
scoring system and multicode length reduced application run time by over 24 percent.
The lower graph on each page shows the performance achieved using the best
technique identified in the upper graph. This graph shows how performing additional
multicode substitutions results in further performance gains by examining the
application’s performance when 10, 20, 30, 40 and 50 multicode substitutions are
performed. The specific list of bytecode sequences replaced with multicodes can be
found in Table A.1 through Table A.6, located in Appendix 11.
Table 7.4 presents a summary of the performance results achieved for each of
the benchmarks. It lists the multicode selection technique and maximum multicode
length that offered the best performance. Each performance value is expressed as a
percentage of the original, unmodified application run time. The table also shows
the average change in performance achieved across the six benchmarks tested. The