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Memory Dependency Prediction (MDP) is paramount to good out-of-order performance, but decidedly not trivial as a all instances of a given static load may not necessarily depend on all instances of a given static store. As a result, for a given load, MDP should predict the exact store instruction the load depends on, and not only whether it depends on an inflight store or not, i.e., ideally, prediction should not be binary. However, we first argue that given the high degree of sophistication of modern branch predictors, the fact that a given dynamic load depends on an inflight store can be captured using the binary prediction capabilities of the branch predictor, providing coarse MDP at zero storage overhead. Second, by leveraging hysteresis counters, we show that the precise producer store can in fact be identified. This embodiment of MDP yields performance levels that are on par with state-of-the-art, and requires less than 70 additional bits of storage over a baseline without MDP at all. [ABSTRACT FROM PUBLISHER]

A new architecture, Early/Out-of-Order/Late Execution (EOLE), leverages value prediction to execute a significant number of instructions outside the out-of-order engine. This approach reduces the issue width, which is a major contributor to both out-of-order engine complexity and the register file port requirement. This reduction paves the way for a truly practical implementation of value prediction [ABSTRACT FROM PUBLISHER]