2014
DOI: 10.1007/978-3-319-10214-6_8
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Toward Better Simulation of MPI Applications on Ethernet/TCP Networks

Abstract: Abstract-Simulation and modeling for performance prediction and profiling is essential for developing and maintaining HPC code that is expected to scale for next-generation exascale systems, and correctly modeling network behavior is essential for creating realistic simulations. In this article we describe an implementation of a flow-based hybrid network model that accounts for factors such as network topology and contention, which are commonly ignored by other approaches. We focus on large-scale, Ethernet-con… Show more

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Cited by 25 publications
(30 citation statements)
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“…Thus, we uphold our resource requirement goal. (2) Second, SMPI builds on the hybrid flow‐level network models of SimGrid that allow to faithfully model communications and contention, which is essential in the context of our study since load balancing in AMPI induces Virtual Process migration that can be costly in terms of communications.…”
Section: Sampi: a Simulation Workflow To Evaluate Ampi Performancementioning
confidence: 99%
“…Thus, we uphold our resource requirement goal. (2) Second, SMPI builds on the hybrid flow‐level network models of SimGrid that allow to faithfully model communications and contention, which is essential in the context of our study since load balancing in AMPI induces Virtual Process migration that can be costly in terms of communications.…”
Section: Sampi: a Simulation Workflow To Evaluate Ampi Performancementioning
confidence: 99%
“…In the HPC context, more precisely regarding MPI applications, SimGrid provides SMPI module [8] which can be used in two different modes: offline and online. In the offline mode, a trace of a previous native execution on a supercomputer is replayed in the simulator.…”
Section: Simgrid Simulation Frameworkmentioning
confidence: 99%
“…In this work we have used the SimGrid simulation framework to model, control, reproduce, and monitor large-scale computing systems to analyze the performance of the DLS algorithms on computationally intensive scientific applications. We have chosen SimGrid to implement the DLS algorithms and to evaluate their robustness because it is a versatile tool and is also validated for the evaluation of scheduling algorithms in distributed and heterogeneous computing systems, such as grids, clouds or peer-to-peer systems [27] [28] [29]. SimGrid's deployment and platform files facilitate the creation of the execution scenarios reflecting load imbalance for performing an experimental evaluation of the robustness of the DLS algorithms.…”
Section: Problemmentioning
confidence: 99%