RT Journal Article
T1 Experiences with nested parallelism in task-parallel applications using malleable BLAS on multicore processors
A1 Castelló, Adrián
A1 Quintana-Ortí, Enrique S.
A1 Rodríguez Sánchez, Rafael
A1 Catalán Pallarés, Sandra
A1 Igual Peña, Francisco Daniel
AB Malleability is defined as the ability to vary the degree of parallelism at runtime, and is regarded as a means to improve core occupation on state-of-the-art multicore processors tshat contain tens of computational cores per socket. This property is especially interesting for applications consisting of irregular workloads and/or divergent executions paths. The integration of malleability in high-performance instances of the Basic Linear Algebra Subprograms (BLAS) is currently nonexistent, and, in consequence, applications relying on these computational kernels cannot benefit from this capability. In response to this scenario, in this paper we demonstrate that significant performance benefits can be gathered via the exploitation of malleability in a framework designed to implement portable and high-performance BLAS-like operations. For this purpose, we integrate malleability within the BLIS library, and provide an experimental evaluation of the result on three different practical use cases.
PB SAGE
YR 2023
FD 2023-03-10
LK https://hdl.handle.net/20.500.14352/115344
UL https://hdl.handle.net/20.500.14352/115344
LA eng
NO Rodríguez-Sánchez R, Castelló A, Catalán S, Igual FD, Quintana-Ortí ES. Experiences with nested parallelism in task-parallel applications using malleable BLAS on multicore processors. The International Journal of High Performance Computing Applications. 2024;38(2):55-68. doi:10.1177/10943420231157653
DS Docta Complutense
RD 9 abr 2025