The Analysis, Measurement and Exploitation of Eager Evaluation in Imperative Instruction Streams

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This research is concerned with dramatically improving the performance of computing machines for traditional languages by increasing the concurrency or parallelism apparent in the input code via eager evaluation. Eager evaluation is the conditional execution of code past conditional branches, before the branches have executed. The specific objectives of the research are to more fully understand and characterize eager evaluation by developing a graph model for its description; measuring the performance gain and resources used when typical codes are executed with eager evaluation, both in an ideal sense to give bounds, and assuming different architectures or execution engines. Also, the development of novel machines to exploit eager evaluation in an efficient manner is to be pursued. One novel aspect of an approach to be followed is to consider the static instruction stream model of execution, in which the code is ordered as it exists in memory, as opposed to just the dynamic, or classic, instruction stream, in which the program counter follows the control flow. The measurements and evaluations to be made will be via computer simulations of the execution of the codes, assuming specific hardware as appropriate.