Framework for a productive performance optimization

Servat, Harald; Llort, Germán; Huck, Kevin; Giménez, Judit; Labarta, Jesús

doi:10.1016/j.parco.2013.05.004

Cited by 24 publications

(19 citation statements)

References 11 publications

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“…As a first step in the performance analysis, we have executed the airplane test case of 31.5M (coarse mesh) on 320 MPI processes using 4 nodes of the POWER9 cluster, running only on the CPUs. For this analysis we have used Extrae [30] to obtain a trace of the execution and Paraver [31] to visualize it (the overhead introduced by the tracing tools is under 4% [32] Figure 4 shows a timeline of a real execution of the airplane simulation. The X-axis represents the time, and the Y-axis represents the different MPI processes.…”

Section: Performance Characterizationmentioning

confidence: 99%

Heterogeneous CPU/GPU co-execution of CFD simulations on the POWER9 architecture: Application to airplane aerodynamics

Borrell

Dosimont

García-Gasulla

et al. 2020

Future Generation Computer Systems

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High fidelity Computational Fluid Dynamics simulations are generally associated with large computing requirements, which are progressively acute with each new generation of supercomputers. However, significant research efforts are required to unlock the computing power of leadingedge systems, currently referred to as pre-Exascale systems, based on increasingly complex architectures. In this paper, we present the approach implemented in the computational mechanics code Alya. We describe in detail the parallelization strategy implemented to fully exploit the different levels of parallelism, together with a novel co-execution method for the efficient utilization of heterogeneous CPU/GPU architectures. The latter is based on a multi-code co-execution approach with a dynamic load balancing mechanism. The assessment of the performance of all the proposed strategies has been carried out for airplane simulations on the POWER9 architecture accelerated with NVIDIA Volta V100 GPUs. * c 2020 Elsevier. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ https://doi.

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Section: Performance Characterizationmentioning

confidence: 99%

Heterogeneous CPU/GPU co-execution of CFD simulations on the POWER9 architecture: Application to airplane aerodynamics

Borrell

Dosimont

García-Gasulla

et al. 2020

Future Generation Computer Systems

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“…Extrae [10] is a tracing tool developed at BSC. It collects information such as PAPI counters, MPI and OpenMP calls during the execution of an application.…”

Section: B Performance Toolsmentioning

confidence: 99%

Performance study of HPC applications on an Arm-based cluster using a generic efficiency model

Banchelli

Peiro

Querol

et al. 2020

2020 28th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP)

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HPC systems and parallel applications are increasing their complexity. Therefore the possibility of easily study and project at large scale the performance of scientific applications is of paramount importance. In this paper we describe a performance analysis method and we apply it to four complex HPC applications. We perform our study on a pre-production HPC system powered by the latest Arm-based CPUs for HPC, the Marvell ThunderX2. For each application we spot inefficiencies and factors that limit their scalability. The results show that in several cases the bottlenecks do not come from the hardware but from the way applications are programmed or the way the system software is configured.

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“…In this section we study a trace of the Alya simulation gathered on one node of the Thunder cluster, introduced in Section 4.2 (i.e., running with 96 MPI processes in the same cluster evaluated in Section 4). We use Extrae [22] to obtain a performance trace and then Paraver [19] to visualize it. In this simulation 4 • 10 5 particles where injected in the respiratory system during the first time step.…”

Section: Profile and Performance Analysismentioning

confidence: 99%

Computational Fluid and Particle Dynamics Simulations for Respiratory System

García-Gasulla

Josep-Fabrego

Eguzkitza

et al. 2018

Proceedings of the 47th International Conference on Parallel Processing Companion

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Computational fluid and particle dynamics simulations (CFPD) are of paramount importance for studying and improving drug effectiveness. Computational requirements of CFPD codes involves high-performance computing (HPC) resources. For these reasons we introduce and evaluate in this paper system software techniques for improving performance and tolerate load imbalance on a stateof-the-art production CFPD code. We demonstrate benefits of these techniques on both Intel-and Arm-based HPC clusters showing the importance of using mechanisms applied at runtime to improve the performance independently of the underlying architecture. We run a real CFPD simulation of particle tracking on the human respiratory system, showing performance improvements of up to 2×, keeping the computational resources constant. CCS CONCEPTS • Computing methodologies → Parallel programming languages; • Applied computing → Systems biology; • Computer systems organization → Multicore architectures; • Hardware → Emerging architectures;

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Framework for a productive performance optimization

Cited by 24 publications

References 11 publications

Heterogeneous CPU/GPU co-execution of CFD simulations on the POWER9 architecture: Application to airplane aerodynamics

Heterogeneous CPU/GPU co-execution of CFD simulations on the POWER9 architecture: Application to airplane aerodynamics

Performance study of HPC applications on an Arm-based cluster using a generic efficiency model

Computational Fluid and Particle Dynamics Simulations for Respiratory System

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