A 64-Kbytes ITTAGE indirect branch predictor∗

The ITTAGE, Indirect Target TAgged GEometric length predictor, was introduced in [5] at the same time as the TAGE conditional branch predictor. ITTAGE relies on the same principles as the TAGE predictor several predictor tables in-dexed through independent functions of the global branch/path history and the branch address. Like the TAGE predictor, ITTAGE uses (partially) tagged components as the PPM-like predictor [2]. It relies on (partial) match to select the predicted target of an indirect jump. TAGE also uses GEometric history length as the O-GEHL predictor [3], i.e., the set of used global history lengths forms a geometric series. This allows to efficiently capture correlation on recent branch outcomes as well as on very old branches. Due to the huge storage budget available for the ChampionShip, we propose an ITTAGE predictor fea-turing 16 prediction tables. On the distributed set of traces, using a path history vector recording only in-formation from indirect jumps and calls was found to be (slightly) more efficient than using a path/branch history vector combining information from all kind of branches. 1 The ITTAGE indirect jump target predictor Building on top of the cascaded predictor [1] and on the TAGE predictor, the ITTAGE predictor was proposed in [4]. In this section, we recall the gen-eral principles of the ITTAGE indirect target pre-dictor.equivalent storage budget. Some implementa-tion details from the initial ITTAGE proposition are slightly modified in order to improve the global pre-diction accuracy. 1.1 ITTAGE predictor principles ITTAGE relies on the same principles as the TAGE predictor several predictor tables indexed through in-dependent functions of the global branch/path his-tory and the branch address. ∗This work was partially supported by the European Re-search Counsil Advanced Grant DA