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Multi-objective hardware-software co-optimization for the SNIPER multi-core simulator

机译:SNIPER多核模拟器的多目标软硬件协同优化

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Modern complex microarchitectures with multicore systems like CPUs, APUs (accelerated processing units) and GPUs require hundreds or thousands of hardware parameters to be fine-tuned to get the best results regarding different objectives like: performance, hardware complexity (integration area), power consumption, temperature, etc. These are only a few of the objectives needed to be taken into consideration when designing a new multicore system. Exploring this huge design space requires special tools like automatic design space exploration frameworks to optimize the hardware parameters. Although the microarchitecture might be very complex, the performance of the applications is also highly dependent on the degree of software optimization. This adds a new challenge to the DSE process. In this paper, using the multi-objective design space exploration tool FADSE, we tried to optimize the hardware and software parameters of the multicore SNIPER simulator running SPLASH-2 benchmarks suite. We optimized the hardware parameters (nr cores, cache sizes, cache associativity, etc.) and software parameters (GCC optimizations, threads, and scheduler) values that have been varied during the DSE process and shown the impact of these parameters on the optimization's multi-objectives (performance, area and power consumption). Furthermore, for the best found Pareto configurations the temperatures will be computed so that in the end we will have a 4-dimensional objective space.
机译:具有CPU,APU(加速处理单元)和GPU等多核系统的现代复杂微体系结构需要对数百或数千个硬件参数进行微调,以获得有关以下目标的最佳结果:性能,硬件复杂性(集成区域),功耗,温度等。这些只是设计新的多核系统时需要考虑的几个目标。要探索如此巨大的设计空间,需要使用诸如自动设计空间探索框架之类的特殊工具来优化硬件参数。尽管微体系结构可能非常复杂,但是应用程序的性能也高度取决于软件优化的程度。这给DSE流程带来了新的挑战。在本文中,我们使用多目标设计空间探索工具FADSE,尝试优化运行SPLASH-2基准套件的多核SNIPER模拟器的硬件和软件参数。我们优化了在DSE流程中变化的硬件参数(nr内核,缓存大小,缓存关联性等)和软件参数(GCC优化,线程和调度程序)的值,并显示了这些参数对优化的多重性的影响。目标(性能,面积和功耗)。此外,对于找到的最佳的Pareto配置,将计算温度,以便最终获得4维目标空间。

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