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The performance of a stack machine is limited mainly by
sequential stackacceses. A performance enhancement mechanism -
Stack Operations Folding -was used in Sun Microelectronics'
picoJava design. There are another twofolding techniques: fixed-
pattern folding and POC model beyond Sun'.In thisthesis, we use
the Java bytecode language as the target machine language,
analyze the factors affecting ILP, and extract parallelism among
bytecodesafter folding using POC model.Five factors: stack
pointer renaming, localvariable renaming, finite operations,
finite scheduling window size andlimited foldable numbers were
simulated and evaluated. Statistical data showthat the ILP can
be doubled as compared to original figure of POC model.
Andwithout stack pointer renaming, the performance gain is only
half oftheoretical upper bound. From the experiments, we observe
that 4 operationsfor each PIG (Parallel Instruction Group) is
enough to approximate thetheoretical upper bound. With a 32-byte
or a 64-byte window size, theperformance can reach 82% or 93% as
compared to the infinite window size.Finally, we conclude that
stack operations folding and stack pointer renamingare the most
important mechanisms in designing higher-end stack machines.
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