Master Thesis

FZJ-2026-03883

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Replay-based Performance Analysis of Nonblocking Collective MPI Operations

Haus, K. (Corresponding author)FZJ*

2026

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Please use a persistent id in citations: doi:10.34734/FZJ-2026-03883

Abstract: The efficient use of large-scale high-performance computing systems requires identifying and eliminating communication bottlenecks, which often manifest as wait states. The Scalasca trace tools automatically detect and quantify such wait states through a replay-based analysis of event traces recorded by Score-P, tracing them back to their root causes and computing the critical path of the execution. While this analysis is well established for blocking collective MPI operations, it does not cover their nonblocking counterparts introduced with MPI-3.This thesis extends Scalasca's replay-based analysis to nonblocking collective MPI operations. The wait-state detection is implemented in Scalasca, and a theoretical concept for synchronization point tracking and the delay and critical-path analyses is developed. The extended tool is evaluated across a range of test cases, demonstrating its capability to identify wait states in nonblocking collective operations and showcasing its practical benefit.

Note: Masterarbeit, FH Aachen - University of Applied Sciences, 2026

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Contributing Institute(s):

1. Jülich Supercomputing Center (JSC)

Research Program(s):

1. 5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs) and Research Groups (POF4-511) (POF4-511)
2. ATMLPP - ATML Parallel Performance (ATMLPP) (ATMLPP)

Appears in the scientific report 2026

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