Understanding the differences between value prediction and instruction reuse

Recently two hardware techniques-Value Prediction (VP) and instruction proposed for exploiting the redundancy in programs to collapse data dependences. In this paper we attempt to understand the different ways in which VP and IR interact with other microarchitectural features and the impact of such interactions on net performance. More specifically we perform the following tasks: (i) we identify, the various differences between the two techniques and qualitatively discuss their microarchitectural interactions, (ii) we evaluate the impact on performance of these interactions, and (iii) since IR is more restrictive of the two techniques, we also estimate the amount of total redundancy, present in programs, that can be captured by IR. Our results show that the performance obtained by VP is sensitive to the way branches with value-speculative operands are handled. We also see that, although IR captures less amount of redundancy, it may perform equally well because it validates results early, it is non-speculative, and it reduces branch misprediction penalty. Finally, we show that 84-97% of redundancy in programs can be reused, implying that the approach of detecting redundant instructions non-speculatively, based on their operands, does not significantly restrict W's ability to capture redundancy present in programs.