A framework to develop symbolic performance models of parallel applications
A framework to develop symbolic performance models of parallel applications
复制标题
开发并行应用程序符号性能模型的框架
DOI：
10.1109/ipdps.2006.1639625
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发表时间：
2006
期刊：
影响因子：
--
通讯作者：
J. Vetter
中科院分区：
文献类型：
--
作者：
S. Alam;J. Vetter
性能和工作负载建模在高端计算生命周期的每个阶段都有许多用途：设计、集成、采购、安装和调整。尽管性能模型非常有用，但它们的构建在很大程度上仍然是一项手工、复杂和耗时的练习。我们提出了一种新的建模方法，称为建模断言(MA)，它借鉴了经验建模技术和分析建模技术的优点。与传统方法相比，该策略具有许多优势：增量构建真实的绩效模型，根据经验数据直接进行模型验证，以及直观地对单个模型项进行误差限制。通过构建浮点运算代价、内存需求和MPI消息量的高保真模型，我们在NAS并行CG和SP基准测试中演示了这种新技术。这些模型由少量关键输入参数驱动，从而允许对未来的问题大小和体系结构进行高效的设计空间探索
Performance and workload modeling has numerous uses at every stage of the high-end computing lifecycle: design, integration, procurement, installation and tuning. Despite the tremendous usefulness of performance models, their construction remains largely a manual, complex, and time-consuming exercise. We propose a new approach to the model construction, called modeling assertions (MA), which borrows advantages from both the empirical and analytical modeling techniques. This strategy has many advantages over traditional methods: incremental construction of realistic performance models, straightforward model validation against empirical data, and intuitive error bounding on individual model terms. We demonstrate this new technique on the NAS parallel CG and SP benchmarks by constructing high fidelity models for the floating-point operation cost, memory requirements, and MPI message volume. These models are driven by a small number of key input parameters thereby allowing efficient design space exploration of future problem sizes and architectures