CYPRESS:结合静态和动态分析的自顶向下通信跟踪压缩

Jidong Zhai, Jianfei Hu, Xiongchao Tang, Xiaosong Ma, Wenguang Chen
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引用次数: 23

摘要

无论是对并行应用程序的性能分析/优化,还是对下一代高性能计算系统的设计,通信轨迹都变得越来越重要。与此同时,超级计算机上的问题规模和执行规模不断增长,产生了大量的通信痕迹。为了减小通信路径的大小,现有的动态压缩方法随着作业规模的增大而引入了较大的压缩开销。我们提出了一种混合静态动态方法,利用从静态分析中获得的信息来促进更有效和高效的动态跟踪压缩。我们提出的方案Cypress在编译时使用程序间分析提取程序通信结构树。该树自然包含关键的迭代计算特性,如循环结构,允许随后的运行时压缩以“自上而下”的方式将事件细节“填充”到已知的通信模板中。结果表明,与最先进的动态方法相比,Cypress将进程内和进程间压缩开销分别降低了5倍和9倍,同时只引入了非常低的编译开销。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CYPRESS: Combining Static and Dynamic Analysis for Top-Down Communication Trace Compression
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.
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