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

Banchelli, Fabio; Peiro, Kilian; Querol, A.; Ramirez-Gargallo, Guillem; Ramirez-Miranda, Guillem; Vinyals, Joan; Vizcaino, Pablo; García-Gasulla, Marta; Mantovani, Filippo

doi:10.1109/pdp50117.2020.00032

Cited by 8 publications

(7 citation statements)

References 11 publications

(13 reference statements)

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“…From the description of the UEABS, the benchmark suite codes are "[...] scalable, currently relevant and publicly available[...], of a size which can realistically run on large systems and maintained into the future". Moreover, from previous works, we know that, in particular input sets, Alya can present a severe load imbalance problem [10] while CP2K shows a communication issue that can limit its scalability [1]. With this selection, we covered the two main metrics we want to demonstrate with TALP: Load balance and Communication efficiency.…”

Section: Environment and Methodologymentioning

confidence: 99%

Talp

López

Miranda

García-Gasulla

2021

Proceedings of the 2021 on Performance EngineeRing, Modelling, Analysis, and VisualizatiOn STrategy

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This paper presents the design, implementation, and application of TALP, a lightweight, portable, extensible, and scalable tool for online parallel performance measurement. The efficiency metrics reported by TALP allow HPC users to evaluate the parallel efficiency of their executions, both post-mortem and at runtime. The API that TALP provides allows the running application or resource managers to collect performance metrics at runtime. This enables the opportunity to adapt the execution based on the metrics collected dynamically. The set of metrics collected by TALP are well defined, independent of the tool, and consolidated. We extend the collection of metrics with two additional ones that can differentiate between the load imbalance originated from the intranode or internode imbalance. We evaluate the potential of TALP with three parallel applications that present various parallel issues and carefully analyze the overhead introduced to determine its limitations. CCS CONCEPTS• Computing methodologies → Parallel computing methodologies; Distributed computing methodologies; • General and reference → Performance; • Computer systems organization → Multicore architectures.

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Section: Environment and Methodologymentioning

confidence: 99%

Talp

López

Miranda

García-Gasulla

2021

Proceedings of the 2021 on Performance EngineeRing, Modelling, Analysis, and VisualizatiOn STrategy

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“…Containers are used in HPC due to portability, composability, and BYOE advantages they offer [221]. Research on performance analysis of HPC applications based on ARM architectures using various ARM-based settings including mobile and cluster evaluated the performance of HPC applications based on portability, energy efficiency, and scalability [222]- [226]. Standard containers like Docker are not suitable for HPC, and this paved the way for the development of HPC-specific container technologies like Singularity [102], Shifter [227], Charliecloud [228], and Sarus [229].…”

Section: A Containers In Hpcmentioning

confidence: 99%

Container Technologies for ARM Architecture: A Comprehensive Survey of the State-of-the-Art

et al. 2022

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Container technology is becoming increasingly popular as an alternative to traditional virtual machines because it provides a faster, lighter, and more portable runtime environment for the applications. A container bundles the application and its binary code, libraries, and configuration files together while sharing the host operating system image. Accordingly, containers efficiently share resources and operate small micro-services, software programs, and even more extensive applications with less overhead than virtual machines. There are many container technologies available with Docker being the most popular and many technologies support multiple architectures, including the ARM architecture. Due to its energy efficiency and high-performance, which are crucial parameters in containerization, ARM architecture is becoming prevalent in container technologies. In this paper, we explore various container technologies that support ARM architecture and investigate the pros and cons of each technology. Moreover, we provide a comparative analysis of both container orchestrators and container runtimes that are most prominent competitors of Docker. We also consider security of container technologies with particular focus on the image scanning tools that supports ARM architecture. Our survey reveals that ARM technology is gaining popularity in containerization and almost all recent technologies support ARM architecture.

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“…This methodology is independent of the tool being used for the analysis and defines a set of performance metrics. These metrics are well defined, accepted by the community, and meaningful, pointing the analysts to the main factors affecting the performance and scalability of the code [49,19]. In this paper, we use some of these metrics as they allow us to compare the different LAMMPS benchmarks using a common ground.…”

Section: Performance Tools and Efficiency Metricsmentioning

confidence: 99%

Hybrid parallelization of molecular dynamics simulations to reduce load imbalance

et al. 2022

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The most widely used technique to allow for parallel simulations in molecular dynamics is spatial domain decomposition, where the physical geometry is divided into boxes, one per processor. This technique can inherently produce computational load imbalance when either the spatial distribution of particles or the computational cost per particle is not uniform. This paper shows the benefits of using a hybrid MPI+OpenMP model to deal with this load imbalance. We consider LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator), a prototypical molecular dynamics simulator that provides its own balancing mechanism and an OpenMP implementation for many of its modules, allowing for a hybrid setup. In this work, we extend the current OpenMP implementation of LAMMPS and optimize it and evaluate three different setups: MPI-only, MPI with the LAMMPS balance mechanism, and hybrid setup using our improved OpenMP version. This comparison is made using the five standard benchmarks included in the LAMMPS distribution plus two additional test cases. Results show that the hybrid approach can deal with load balancing problems better and more effectively (50% improvement versus MPI-only for a highly-imbalanced testcase) than the LAMMPS balance mechanism (only 43% improvement) and improve simulations with issues other than load imbalance.

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

Cited by 8 publications

References 11 publications

Talp

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Container Technologies for ARM Architecture: A Comprehensive Survey of the State-of-the-Art

Hybrid parallelization of molecular dynamics simulations to reduce load imbalance

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