OPTIMIZING THE JAVA VIRTUAL MACHINE INSTRUCTION SET BY ...

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amount of time that must be spent matching bytecode sequences against the code
stream within the class file at runtime.
10.2.7 Testing Additional Computational Environments
The multicode work presented in this thesis considered only one virtual machine
executing on one computing platform. This test environment must be expanded
in order to determine how wide ranging the benefits of multicodes are. Additional
platforms that should be tested include desktop and server platforms with virtual
machines that make use of a JIT compiler, possibly in conjunction with an interpreter.
Examining smaller computing environments will also be interesting. While multicodes
shrink code size by reducing the number of opcodes present in the code stream,
the number of distinct opcodes increases, requiring a larger virtual machine. Conducting
a study to determine where the balance between these competing factors lies
will have interesting results with respect to the Java instruction set and the design of
future instruction sets for resource constrained environments.
Finally, it would be interesting to consider a hardware implementation of multicodes.
Trade-offs that would need to be considered include the performance of the
chip compared to the complexity of its implementation, its size and the amount of
power it consumes. Future work in this area could also examine the idea of using field
programmable devices that dynamically modify themselves to support the instruction
set in use by the application currently being executed.
10.2.8 Handling Parallelism
The profiling framework implemented as part of both the despecialization and multicode
work is not currently thread-safe. Consequently, multi-threaded applications
cannot be profiled. This limitation prevented 227 mtrt from being considered from
the SPEC JVM98 Benchmark Suite and made it impossible to consider the benchmarks
in the newer Java Grande Parallel Benchmark Suite [99, 100]. This limitation
does not just impact the ability of multicodes to be applied to a select set of benchmarks.
It must be overcome in order to profile many of the real world applications
that are executed by “typical” users.