DRCCTPROF: A Fine-Grained Call Path Profiler for ARM-Based Clusters

Qidong Zhao, Xu Liu, Milind Chabbi
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引用次数: 2

Abstract

ARM is an attractive CPU architecture for exascale systems because of its energy efficiency. As a recent entry into the HPC paradigm, ARM lags in its software stack, especially in the performance tooling aspect. Notably, there is a lack of fine-grained measurement tools to analyze fully optimized HPC binary executables on ARM processors. In this paper, we introduce DRCCTPROF — a fine-grained call path profiling framework for binaries running on ARM architectures. The unique ability of DRCCTPROF is to obtain full calling context at any and every machine instruction that executes, which provides more detailed diagnostic feedback for performance optimization and correctness tools. Furthermore, DRCCTPROF not only associates any instruction with source code along the call path, but also associates memory access instructions back to the constituent data object. Finally, DRCCTPROF incurs moderate overhead and provides a compact view to visualize the profiles collected from parallel executions.
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DRCCTPROF:基于arm集群的细粒度调用路径分析器
对于百亿亿级系统来说,ARM是一种很有吸引力的CPU架构,因为它的能效很高。作为一个新近进入高性能计算范式的人,ARM在软件堆栈方面落后,尤其是在性能工具方面。值得注意的是,缺乏细粒度的测量工具来分析ARM处理器上完全优化的HPC二进制可执行文件。在本文中,我们介绍了DRCCTPROF——一个用于运行在ARM架构上的二进制文件的细粒度调用路径分析框架。DRCCTPROF的独特功能是在执行的任何一条机器指令中获得完整的调用上下文,这为性能优化和正确性工具提供了更详细的诊断反馈。此外,DRCCTPROF不仅沿着调用路径将任何指令与源代码关联起来,而且还将内存访问指令关联回组成数据对象。最后,DRCCTPROF带来了适度的开销,并提供了一个紧凑的视图来可视化从并行执行中收集的概要文件。
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