CAREER: rePLay: a Microarchitecture to Support Dynamic Program Optimization

动态优化是计算机系统研究的一个新兴领域，它为计算机性能的大幅提高提供了良好的潜力。动态优化的关键是将仅在执行时可用的动态信息合并到优化过程中。潜在有用的动态信息的例子包括分支的可能行为和操作数的可能值。与传统的静态优化器相比，更直接地访问运行时信息为动态优化器提供了显著的优势。重放框架是一组支持动态优化的微体系结构组件。Replay包含允许动态优化器与程序执行并行运行的硬件，从而减少了与动态优化相关的大量开销。Replay包含用于识别候选区域、用于优化这些区域、获取区域以及它们之间的排序的硬件。此外，这种微体系结构在优化器和检测运行时事件的硬件之间创建了紧密耦合。初步结果表明，动态信息可用于创建非常长(约100条指令)的原子、单入口、单出口代码区域用于优化。研究重点是重放框架的开发，特别是基于硬件的优化和硬件方案的开发，以支持潜在的基于推测值的优化。

Dynamic optimization is a newly emerging area of computer systems research that offers good potential for large advances in computer performance. The crux of dynamic optimization is the incorporation of dynamic information available only at execution time into the optimization process. Examples of potentially useful dynamic information include the likely behavior of branches and the likely values of operands. More immediate access to run-time information gives dynamic optimizers a notable edge over traditional static optimizers.The rePLay Framework is a set of microarchitectural components for supporting dynamic optimization. RePLay contains hardware that allows the dynamic optimizer to run in parallel with program execution thereby reducing the large overheads associated with dynamic optimization. RePLay contains hardware for identifying candidate regions, for optimizing these regions, fetching regions, and sequencing between them. Furthermore, this microarchitecture creates a tight coupling between the optimizer and hardware that detects run-time events. Initial results indicate that dynamic information can be used to create very long (approx 100 instructions) atomic, single entry, single exit regions of code for optimization.The research focuses on the development of the rePLay Framework, specifically in the development ofhardware-based optimizations and hardware schemes to support potentially speculative value-based optimizations.