ARM ISA-based processors are no longer low-cost, low-power processors. Nowadays, ARM ISA-based processor manufacturers are striving to implement medium-end to high-end processor cores, which implies implementing a state-of-the-art out-of-order execution engine. Unfortunately, providing efficient out-of-order execution on legacy ARM codes may be quite challenging due to guarded instructions. Predicting the guarded instructions addresses the main serialization impact associated with guarded instructions execution and the multiple definition problem. Moreover, guard prediction allows one to use a global branch-and-guard history predictor to predict both branches and guards, often improving branch prediction accuracy. Unfortunately, such a global branch-and-guard history predictor requires the systematic use of guard predictions. In that case, poor guard prediction accuracy would lead to poor overall performance on some applications. Building on top of recent advances in branch prediction and confidence estimation, we propose a hybrid branch-and-guard predictor, combining a global branch history component and global branch-and-guard history component. The potential gain or loss due to the systematic use of guard prediction is dynamically evaluated at runtime. Two computing modes are enabled: systematic guard prediction use and high-confidence-only guard prediction use. Our experiments show that on most applications, an overwhelming majority of guarded instructions are predicted. Therefore, a simple but relatively inefficient hardware solution can be used to execute the few unpredicted guarded instructions. Significant performance benefits are observed on most applications, while applications with poorly predictable guards do not suffer from performance loss.

In the multicore era, achieving ultimate single process performance is still an issue e.g. for single process workload or for sequential sections in parallel applications. Unfortunately, despite tremendous research effort on branch prediction, substantial performance potential is still wasted due to branch mispredictions. On a branch misprediction resolution, instruction treatment on the wrong path is essentially thrown away. However, in most cases after a conditional branch, the taken and the not-taken paths of execution merge after a few instructions. Instructions that follow the reconvergence point are executed whatever the branch outcome is. We present SYRANT (SYmmetric Resource Allocation on Not-taken and Taken paths), a new technique for exploiting control independence. SYRANT essentially uses the same pipeline structure as a conventional processor. SYRANT tries to enforce the allocation of the exact same resources on the out-of-order execution mechanism (physical register, load/store queue and reorder buffer) for both the taken and not-taken paths. Thus, on a branch misprediction, the result of an instruction already executed on the wrong path after the reconvergence point can be conserved in the same structure when it is data independent. Adding SYRANT on top of an aggressive superscalar execution core allows to improve performance for applications suffering a significant branch misprediction rate. As a side, but important extra contribution, we introduce ABL/SBL a simple and non-intrusive hardware reconvergence detection mechanism. ABL/SBL can be used in a conventional superscalar processor to improve branch prediction accuracy by exploiting the execution of branches along the wrong path.