Performance and energy effects on task-based parallelized applications

Autor:	Diego Caballero, Roger Ferrer, Marc Casas, Mateo Valero, Juan M. Cebrian, Helena Caminal, Xavier Martorell, Miquel Moreto
Přispěvatelé:	Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors, Barcelona Supercomputing Center, Universitat Politècnica de Catalunya. CAP - Grup de Computació d'Altes Prestacions
Rok vydání:	2018
Předmět:	Data parallelism Computer science 020209 energy Microprocessors -- Energy consumption Task-level parallelism 02 engineering and technology Parallel computing Data-level parallelism Theoretical Computer Science Software portability Vectorization 0202 electrical engineering electronic engineering information engineering SIMD Informàtica::Arquitectura de computadors::Arquitectures paral·leles [Àrees temàtiques de la UPC] Programmer 020203 distributed computing Parallel processing (Electronic computers) Processament en paral·lel (Ordinadors) Vector processing (Computer science) Task (computing) Energy efficiency Microprocessadors -- Consum d'energia Hardware and Architecture Vectorization (mathematics) Scalability Programming paradigm Software Information Systems
Zdroj:	UPCommons. Portal del coneixement obert de la UPC Universitat Politècnica de Catalunya (UPC) Recercat. Dipósit de la Recerca de Catalunya instname
ISSN:	1573-0484 0920-8542
DOI:	10.1007/s11227-018-2294-9
Popis:	Heterogeneity, parallelization and vectorization are key techniques to improve the performance and energy efficiency of modern computing systems. However, programming and maintaining code for these architectures poses a huge challenge due to the ever-increasing architecture complexity. Task-based environments hide most of this complexity, improving scalability and usage of the available resources. In these environments, while there has been a lot of effort to ease parallelization and improve the usage of heterogeneous resources, vectorization has been considered a secondary objective. Furthermore, there has been a swift and unstoppable burst of vector architectures at all market segments, from embedded to HPC. Vectorization can no longer be ignored, but manual vectorization is tedious, error-prone and not practical for the average programmer. This work evaluates the feasibility of user-directed vectorization in task-based applications. Our evaluation is based on the OmpSs programming model, extended to support user-directed vectorization for different SIMD architectures (i.e., SSE, AVX2, AVX512). Results show that user-directed codes achieve manually optimized code performance and energy efficiency with minimal code modifications, favoring portability across different SIMD architectures.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::219487f7f9d1daee1c9c99f1277dc672 https://doi.org/10.1007/s11227-018-2294-9 Zobrazit plný text záznamu Plný text ve formátu PDF Plný text ve formátu HTML
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