A gem5 trace-driven simulator for fast architecture exploration of OpenMP workloads

Alejandro Nocua 1 Florent Bruguier 1 Gilles Sassatelli 1 Abdoulaye Gamatié 1
1 ADAC - ADAptive Computing
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : Architecture parameter exploration is one of the main analysis that needs to be performed in order to ensure that a multicore system has an optimal set of parameters. The main drawback of current simulation approaches is the long simulation times in order to extract performance metrics while varying a system parameter. Trace-driven simulation approaches allow to abstract selected components of the system under analysis by creating traces during the execution time of an application. This technique reduces the simulation time while keeping the accuracy levels. Even tough trace-driven techniques have proven to be useful, most of them are focused on mono-core systems, and some do not completely capture the behavior of multi-threaded programs. In this regard, we developed a trace-driven simulation approach based on the gem5 framework. This approach is based on a collection phase of the instructions and dependencies of a given application and two extra traces depending on the selected analysis. It allows weak and strong scaling analysis along with the possibility to perform extensive parameter exploration analysis. For weak scaling analysis simulations, we collect synchronization traces for OpenMP applications, and for strong scaling analysis, we collect task traces for OmpSs applications.
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-02100235
Contributor : Abdoulaye Gamatié <>
Submitted on : Monday, April 15, 2019 - 4:32:08 PM
Last modification on : Monday, July 15, 2019 - 11:11:16 AM

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Alejandro Nocua, Florent Bruguier, Gilles Sassatelli, Abdoulaye Gamatié. A gem5 trace-driven simulator for fast architecture exploration of OpenMP workloads. Microprocessors and Microsystems: Embedded Hardware Design (MICPRO), Elsevier, 2019, 67, pp.42-55. ⟨10.1016/j.micpro.2019.01.008⟩. ⟨lirmm-02100235⟩

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