SC2025Top-tier venue
TraceFlow: Efficient Trace Analysis for Large-Scale Parallel Applications via Interaction Pattern-Aware Trace Distribution
Yuyang Jin, Xirui Shui, Mingshu Zhai, Zan Zong, Feng Zhang, Felix Wolf, Jidong Zhai
Abstract
Trace analysis of large-scale parallel applications is crucial for understanding and optimizing performance. It primarily focuses on the interaction behaviors between different parallel processes, such as synchronization waits and asynchronous overlaps. The trace size explodes as the parallel scale of applications, thus current methods analyze traces in parallel to ensure analysis speed. However, due to the interaction pattern-agnostic trace distribution, they often introduce inter-process communications to fetch non-local event data during interaction analysis, leading to excessively long trace analysis time.
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