Multithreaded Dense Linear Algebra on Asymmetric Multi-core Processors

This dissertation targets two important problems. The first one is the design of low-level DLA kernels for architectures comprising two (or more) classes of cores. The main question we have to address here is how to attain a balanced distribution of the computational workload among the heterogeneous...

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Detalles Bibliográficos
Autor: Catalán Pallarés, Sandra
Tipo de recurso: tesis doctoral
Estado:Versión publicada
Fecha de publicación:2018
País:España
Institución:CBUC, CESCA
Repositorio:TDR. Tesis Doctorales en Red
OAI Identifier:oai:www.tdx.cat:10803/461918
Acceso en línea:http://hdl.handle.net/10803/461918
http://dx.doi.org/10.6035/14101.2018.209077
Access Level:acceso abierto
Palabra clave:Dense Linear Algebra
Asymmetric Multi-core Processors
HPC
BLAS
LAPACK
Thread-Level Malleability
Enginyeria, Indústria i Construcció
004
512
Descripción
Sumario:This dissertation targets two important problems. The first one is the design of low-level DLA kernels for architectures comprising two (or more) classes of cores. The main question we have to address here is how to attain a balanced distribution of the computational workload among the heterogeneous cores while taking into account that some of the resources, in particular cache levels, are either shared or private. The second question is partially related to the first one. Concretely, this dissertation explores an alternative to runtime-based systems in order to extract “sufficient" parallelism from complex DLA operations while making an efficient use of the cache hierarchy of the architecture. Thus, the main goal of this thesis is the study, design, development and analysis of experimental solutions that are architecture-aware for the execution of DLA operations on low power architectures, more specically asymmetric platforms.