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Eager Scheduling of Dependent Instructions

2022
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Thesis / Dissertation Description

Modern superscalar processors are able to potentially issue and execute multiple instructions per cycle. Several techniques over the years have focused on increasing the Instruction Level Parallelism (ILP) that a processor can exploit. However, there are many limitations of ILP that hinder performance, chief of them being the chain of dependencies between instructions that stops instructions from being executed in parallel.We propose a new micro-architecture design which extends the superscalar pipeline with a data-flow pipeline where the dataflow part identifies immediately dependent instructions and executes them early. The dataflow pipeline is able to identify redundant instructions, track changes in the operands of the redundant instructions and execute new instructions early in case of operand change. Our design helps alleviate some of the main limitations of ILP.

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