用于架构和编译器探索的基准综合

Luk Van Ertvelde, L. Eeckhout
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引用次数: 27

摘要

本文提出了一种新的基准综合框架,它具有三个关键特征。首先,它用一种高级编程语言(在我们的例子中是C语言)生成综合基准,而之前的基准合成工作是用汇编语言生成综合基准。其次,合成基准对构建它们的原始工作负载隐藏专有信息。因此,公司可能希望将合成基准克隆分发给第三方,作为其专有代码的代理;然后,第三方可以在没有访问原始代码的情况下优化目标系统。第三,合成基准比它们所建模的原始工作负载运行时间更短,但它们具有代表性。总之,建议的框架生成小型(因此可以快速模拟)和代表性基准,可以作为其他工作负载的代理,而不会泄露专有信息;由于基准测试是用高级编程语言生成的,因此可以使用它们来探索体系结构和编译器空间。使用我们的初始框架获得的结果是有希望的。我们演示了我们可以为MiBench基准测试生成合成代理基准测试,并且我们展示了它们在具有不同指令集架构、微架构、编译器和优化级别的一系列机器上具有代表性,同时平均运行时间缩短了30倍。我们还使用软件剽窃检测工具验证了合成基准克隆对原始工作负载隐藏了专有信息。
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Benchmark synthesis for architecture and compiler exploration
This paper presents a novel benchmark synthesis framework with three key features. First, it generates synthetic benchmarks in a high-level programming language (C in our case), in contrast to prior work in benchmark synthesis which generates synthetic benchmarks in assembly. Second, the synthetic benchmarks hide proprietary information from the original workloads they are built after. Hence, companies may want to distribute synthetic benchmark clones to third parties as proxies for their proprietary codes; third parties can then optimize the target system without having access to the original codes. Third, the synthetic benchmarks are shorter running than the original workloads they are modeled after, yet they are representative. In summary, the proposed framework generates small (thus quick to simulate) and representative benchmarks that can serve as proxies for other workloads without revealing proprietary information; and because the benchmarks are generated in a high-level programming language, they can be used to explore both the architecture and compiler spaces. The results obtained with our initial framework are promising. We demonstrate that we can generate synthetic proxy benchmarks for the MiBench benchmarks, and we show that they are representative across a range of machines with different instruction-set architectures, microarchitectures, and compilers and optimization levels, while being 30 times shorter running on average. We also verify using software plagiarism detection tools that the synthetic benchmark clones hide proprietary information from the original workloads.
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