OPTIMIZING THE JAVA VIRTUAL MACHINE INSTRUCTION SET BY ...

65
Test Total Weighted
Condition Performance Average
Change (s) (Percent)
Base 0.00 0.00
Load -0.26 -0.15
Store 1.36 0.78
Load Store 0.74 0.42
Branch -2.38 -1.36
Constant 0.43 0.25
Constant Widening -0.98 -0.56
LSC 0.17 0.10
LSCB -2.04 -1.17
Complete -3.89 -2.23
Table 4.8: RVM Performance
tual machine would be smaller than those observed for the Kaffe interpreter. This
assessment is based on the fact that many of the despecializations performed will not
impact the final machine code generated by the JIT compiler.
Consider the following example. When a specialized load bytecode is converted to
machine code the JIT compiler generates the machine language instructions necessary
to load the local variable specified by the opcode. When a general purpose load
bytecode is compiled, the same instructions are generated to copy the value from
the local variable storage to the stack. In this case, the position that is copied is
dictated by an operand in the code stream. However, this operand is a constant value
that cannot change during the execution of the application. Consequently, when
JIT compilation is performed, the operand specifying the local variable to load can
be used directly, generating machine code that is just as efficient as that generated
for the specialized bytecode. The only overhead introduced as a consequence of this
despecialization is the small amount of extra work that must be performed during JIT
compilation to decode the operand specifying the local variable and the extra time
related to loading the despecialized class file which is slightly larger than the original
class file. Each of the operations that have extra costs associated with them occur
once when the application is executed. In an interpreter, the overhead associated
with decoding extra operands are imposed every time the despecialized bytecodes are
executed, causing the overhead to impact the performance of the application many
times throughout its execution.
Table 4.8 shows a summary of the performance results observed when the IBM’s
RVM was tested. It is observed that performing Complete despecialization slows the