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CYPRESS: Combining Static and Dynamic Analysis for Top-Down Communication Trace Compression

机译:CYPRESS:结合静态和动态分析进行自上而下的通信轨迹压缩

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Communication traces are increasingly important, both for parallel applications' performance analysis/optimization, and for designing next-generation HPC systems. Meanwhile, the problem size and the execution scale on supercomputers keep growing, producing prohibitive volume of communication traces. To reduce the size of communication traces, existing dynamic compression methods introduce large compression overhead with the job scale. We propose a hybrid static-dynamic method that leverages information acquired from static analysis to facilitate more effective and efficient dynamic trace compression. Our proposed scheme, Cypress, extracts a program communication structure tree at compile time using inter-procedural analysis. This tree naturally contains crucial iterative computing features such as the loop structure, allowing subsequent runtime compression to "fill in", in a "top-down" manner, event details into the known communication template. Results show that Cypress reduces intra-process and inter-process compression overhead up to 5× and 9× respectively over state-of-the-art dynamic methods, while only introducing very low compiling overhead.
机译:通信迹线对于并行应用程序的性能分析/优化以及设计下一代HPC系统都变得越来越重要。同时,超级计算机上的问题规模和执行规模不断增长,从而产生了过多的通信痕迹。为了减小通信迹线的大小,现有的动态压缩方法随着工作规模引入了较大的压缩开销。我们提出一种混合静态-动态方法,该方法利用从静态分析中获取的信息来促进更有效的动态跟踪压缩。我们提出的方案Cypress,使用过程间分析在编译时提取程序通信结构树。该树自然包含关键的迭代计算功能,例如循环结构,从而允许后续运行时压缩以“自上而下”的方式将事件详细信息“填充”到已知的通信模板中。结果表明,与最新的动态方法相比,赛普拉斯将进程内和进程间压缩开销分别降低了5倍和9倍,而仅引入了非常低的编译开销。

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