TALP - A Lightweight Tool to Unveil Parallel Efficiency of Large-scale Executions
Autor: | Marta Garcia-Gasulla, Victor Lopez, Guillem Ramirez Miranda |
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Přispěvatelé: | Barcelona Supercomputing Center |
Rok vydání: | 2021 |
Předmět: |
020203 distributed computing
Computer science Performance and optimization Scale (chemistry) Distributed computing 02 engineering and technology Supercomputers Performance Monitoring Extensibility Set (abstract data type) Resource (project management) Supercomputadors Parallel computer programs Scalability 0202 electrical engineering electronic engineering information engineering Overhead (computing) Performance monitoring 020201 artificial intelligence & image processing Performance measurement High performance computing Distributed computing systems Heterogeneous Informàtica::Arquitectura de computadors::Arquitectures paral·leles [Àrees temàtiques de la UPC] Informàtica::Programació [Àrees temàtiques de la UPC] |
Zdroj: | Proceedings of the 2021 on Performance EngineeRing, Modelling, Analysis, and VisualizatiOn STrategy UPCommons. Portal del coneixement obert de la UPC Universitat Politècnica de Catalunya (UPC) |
DOI: | 10.1145/3452412.3462753 |
Popis: | 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. This work is partially supported by the Spanish Government through Programa Severo Ochoa (SEV-2015-0493), by the Spanish Ministry of Science and Technology (TIN2015-65316-P), by the Generalitat de Catalunya (2017-SGR-1414), and by the European POP CoE (GA n. 824080). |
Databáze: | OpenAIRE |
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