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An agree predictor is a two-level adaptive predictor with globally shared history buffer and pattern history table, and an additional local saturating counter. The outputs of the local and the global predictors are XORed with each other to give the final prediction.
The local predictor is a two-level table which records the history of individual branches. It consists of a 1,024-entry by 10-bit branch history table. A two-level table was used as the prediction accuracy is similar to that of a larger single-level table while requiring fewer bits of storage. It has a 1,024-entry branch prediction table.
The general rule for a two-level adaptive predictor with an n-bit history is that it can predict any repetitive sequence with any period if all n-bit sub-sequences are different.[8] The advantage of the two-level adaptive predictor is that it can quickly learn to predict an arbitrary repetitive pattern.
When computing a t-test, it is important to keep in mind the degrees of freedom, which will depend on the level of the predictor (e.g., level 1 predictor or level 2 predictor). [5] For a level 1 predictor, the degrees of freedom are based on the number of level 1 predictors, the number of groups and the number of individual observations. For a ...
The use of a sequence of experiments, where the design of each may depend on the results of previous experiments, including the possible decision to stop experimenting, is within the scope of sequential analysis, a field that was pioneered [12] by Abraham Wald in the context of sequential tests of statistical hypotheses. [13]
This approach is employed in a variety of areas, including branch prediction in pipelined processors, value prediction for exploiting value locality, prefetching memory and files, and optimistic concurrency control in database systems. [1] [2] [3] Speculative multithreading is a special case of speculative execution.
Historically, branch prediction took statistics, and used the result to optimize code. A programmer would compile a test version of a program, and run it with test data. The test code counted how the branches were actually taken. The statistics from the test code were then used by the compiler to optimize the branches of released code.
With predication, all possible branch paths are coded inline, but some instructions execute while others do not. The basic idea is that each instruction is associated with a predicate (the word here used similarly to its usage in predicate logic) and that the instruction will only be executed if the predicate is true.