Approximating Pareto optimal compiler optimization sequences—a trade‐off between WCET, ACET and code size

Abstract

SUMMARY With the growing complexity of embedded systems software, high code quality can only be achieved using a compiler. Sophisticated compilers provide a vast spectrum of various optimizations to improve code aggressively w.r.t. different objective functions, e.g. average‐case execution time (ACET) or code size. Owing to the complex interactions between the optimizations, the choice for a promising sequence of code transformations is not trivial. Compiler developers address this problem by proposing standard optimization levels, e.g. O3 or Os. However, previous studies have shown that these standard levels often miss optimization potential or might even result in performance degradation. In this paper, we propose the first adaptive worst‐case execution time (WCET)‐aware compiler framework for an automatic search of compiler optimization sequences that yield highly optimized code. Besides the objective functions ACET and code size, we consider the WCET which is a crucial parameter for real‐time systems. To find suitable trade‐offs between these objectives, stochastic evolutionary multi‐objective algorithms identifying Pareto optimal solutions for the objectives 〈WCET, ACET 〉 and 〈WCET, code size 〉 are exploited. A comparison based on statistical performance assessments is performed that helps to determine the most suitable multi‐objective optimizer. The effectiveness of our approach is demonstrated on real‐life benchmarks showing that standard optimization levels can be significantly outperformed. Copyright © 2011 John Wiley & Sons, Ltd.

Reconciling Compiler Optimizations and WCET Estimation Using Iterative Compilation

“…It is used in design space exploration to evaluate the fidelity of a model compared to the actual system. In this work we use it to evaluate the quality of the ordering at a given unrolling factor compared to our reference, a virtual unrolling of 32 in Figure 16, a coefficient of 1 being a perfect ranking. We observe that we reach good rankings when the estimated WCET reaches a plateau in Figure 14.…”

“…When using source-level flow annotations for WCET estimation, these annotations have to be transformed together with code transformations [24], [30]- [32]. From an engineering perspective, tracing flow information in a compiler, albeit opensource, is a time-consuming task and the flow fact traceability code has to be maintained and be consistent alongside the code of the optimizations.…”

Identifying Compiler Options to Minimize Energy Consumption for Embedded Platforms

“…While these techniques are shown to be effective, they have the drawback that the reasons behind an optimisation's selection is not obvious. Another study [30] has explored genetic algorithms in the context of optimising multiple objectives. This study used the technique to balance the tradeoff between code size, performance and worst-case performance, and could also optimise for any single objective at the cost of the others.…”

Selection of compiler-optimization sequences

“…除此之外, 为了在目标代码执行速度和代码规模等优化目标之间有所权衡, 研究人员使用一些多 目标优化算法来选择待编译程序对应的编译优化序列. Lokuciejewski 等 [15,16] 分析了多目标优化算法 在编译优化序列选择中的应用情况, 其使用 SPEA2, NSGA-II 和 IBEA 为待编译程序选择满足目标代 码执行速度、规模等目标的编译优化序列. 实验表明这些多目标优化算法相比于标准优化序列获得了 显著的提升.…”