Speculative Parallelization in Decoupled Look-ahead

While a canonical out-of-order engine can effectively exploit implicit parallelism in sequential programs, its ef-fectiveness is often hindered by instruction and data supply imperfections manifested as branch mispredictions and cache misses. Accurate and deep look-ahead guided by a slice of the executed program is a simple yet effective approach to mitigate the performance impact of branch mispredictions and cache misses. Unfortunately, program slice-guided look-ahead is often limited by the speed of the look-ahead code slice, especially for irregular programs. In this paper, we attempt to speed up the look-ahead agent using specula-tive parallelization, which is especially suited for the task. First, slicing for look-ahead tends to reduce important data dependences that prohibit successful speculative paralleliza-tion. Second, the task for look-ahead is not correctness-critical and thus naturally tolerates dependence violations. This enables an implementation to forgo violation detection altogether, simplifying architectural support tremendously. In a straightforward implementation, incorporating speculative parallelization to the look-ahead agent further improves sys-tem performance by up to 1.39x with an average of 1.13x. Keywords-Decoupled look-ahead; Speculative paralleliza-tion; Helper-threading; Microarchitectur