Matches in SemOpenAlex for { <https://semopenalex.org/work/W4309341372> ?p ?o ?g. }
- W4309341372 endingPage "123649" @default.
- W4309341372 startingPage "123649" @default.
- W4309341372 abstract "We assess the performance of the hybrid Open Accelerator (OpenACC) and Message Passing Interface (MPI) approach for multi-graphics processing units (GPUs) accelerated thermal lattice Boltzmann (LB) simulation. The OpenACC accelerates computation on a single GPU, and the MPI synchronizes the information between multiple GPUs. With a single GPU, the two-dimension (2D) simulation achieved 1.93 billion lattice updates per second (GLUPS) with a grid number of $8193^{2}$, and the three-dimension (3D) simulation achieved 1.04 GLUPS with a grid number of $385^{3}$, which is more than 76% of the theoretical maximum performance. On multi-GPUs, we adopt block partitioning, overlapping communications with computations, and concurrent computation to optimize parallel efficiency. We show that in the strong scaling test, using 16 GPUs, the 2D simulation achieved 30.42 GLUPS and the 3D simulation achieved 14.52 GLUPS. In the weak scaling test, the parallel efficiency remains above 99% up to 16 GPUs. Our results demonstrated that, with improved data and task management, the hybrid OpenACC and MPI technique is promising for thermal LB simulation on multi-GPUs." @default.
- W4309341372 created "2022-11-26" @default.
- W4309341372 creator A5022770337 @default.
- W4309341372 creator A5032005955 @default.
- W4309341372 date "2023-02-01" @default.
- W4309341372 modified "2023-10-16" @default.
- W4309341372 title "Multi-GPU thermal lattice Boltzmann simulations using OpenACC and MPI" @default.
- W4309341372 cites W1603142303 @default.
- W4309341372 cites W1971144721 @default.
- W4309341372 cites W1976346389 @default.
- W4309341372 cites W1988271670 @default.
- W4309341372 cites W1995432234 @default.
- W4309341372 cites W2012928711 @default.
- W4309341372 cites W2014743572 @default.
- W4309341372 cites W2016716665 @default.
- W4309341372 cites W2017752046 @default.
- W4309341372 cites W2039431421 @default.
- W4309341372 cites W2042497845 @default.
- W4309341372 cites W2048393105 @default.
- W4309341372 cites W2074129693 @default.
- W4309341372 cites W2077508082 @default.
- W4309341372 cites W2087700647 @default.
- W4309341372 cites W2092687851 @default.
- W4309341372 cites W2105366533 @default.
- W4309341372 cites W2108238461 @default.
- W4309341372 cites W2116951845 @default.
- W4309341372 cites W2117242079 @default.
- W4309341372 cites W2120900954 @default.
- W4309341372 cites W2171847398 @default.
- W4309341372 cites W2312670153 @default.
- W4309341372 cites W2320559324 @default.
- W4309341372 cites W2547371652 @default.
- W4309341372 cites W2591376489 @default.
- W4309341372 cites W2800410438 @default.
- W4309341372 cites W2953139132 @default.
- W4309341372 cites W2963709216 @default.
- W4309341372 cites W2999537838 @default.
- W4309341372 cites W3019043644 @default.
- W4309341372 cites W3030255514 @default.
- W4309341372 cites W3033308515 @default.
- W4309341372 cites W3034793926 @default.
- W4309341372 cites W3106170021 @default.
- W4309341372 cites W3106440809 @default.
- W4309341372 cites W3121525383 @default.
- W4309341372 cites W3122264676 @default.
- W4309341372 cites W3183290118 @default.
- W4309341372 cites W3202772396 @default.
- W4309341372 cites W4224640186 @default.
- W4309341372 cites W4305082778 @default.
- W4309341372 cites W91326519 @default.
- W4309341372 doi "https://doi.org/10.1016/j.ijheatmasstransfer.2022.123649" @default.
- W4309341372 hasPublicationYear "2023" @default.
- W4309341372 type Work @default.
- W4309341372 citedByCount "9" @default.
- W4309341372 countsByYear W43093413722023 @default.
- W4309341372 crossrefType "journal-article" @default.
- W4309341372 hasAuthorship W4309341372A5022770337 @default.
- W4309341372 hasAuthorship W4309341372A5032005955 @default.
- W4309341372 hasBestOaLocation W43093413722 @default.
- W4309341372 hasConcept C11413529 @default.
- W4309341372 hasConcept C121332964 @default.
- W4309341372 hasConcept C121684516 @default.
- W4309341372 hasConcept C166782233 @default.
- W4309341372 hasConcept C173608175 @default.
- W4309341372 hasConcept C187691185 @default.
- W4309341372 hasConcept C21442007 @default.
- W4309341372 hasConcept C21821499 @default.
- W4309341372 hasConcept C2524010 @default.
- W4309341372 hasConcept C2777210771 @default.
- W4309341372 hasConcept C2778119891 @default.
- W4309341372 hasConcept C2779851693 @default.
- W4309341372 hasConcept C33923547 @default.
- W4309341372 hasConcept C41008148 @default.
- W4309341372 hasConcept C45374587 @default.
- W4309341372 hasConcept C459310 @default.
- W4309341372 hasConcept C62520636 @default.
- W4309341372 hasConcept C83283714 @default.
- W4309341372 hasConcept C854659 @default.
- W4309341372 hasConcept C99844830 @default.
- W4309341372 hasConceptScore W4309341372C11413529 @default.
- W4309341372 hasConceptScore W4309341372C121332964 @default.
- W4309341372 hasConceptScore W4309341372C121684516 @default.
- W4309341372 hasConceptScore W4309341372C166782233 @default.
- W4309341372 hasConceptScore W4309341372C173608175 @default.
- W4309341372 hasConceptScore W4309341372C187691185 @default.
- W4309341372 hasConceptScore W4309341372C21442007 @default.
- W4309341372 hasConceptScore W4309341372C21821499 @default.
- W4309341372 hasConceptScore W4309341372C2524010 @default.
- W4309341372 hasConceptScore W4309341372C2777210771 @default.
- W4309341372 hasConceptScore W4309341372C2778119891 @default.
- W4309341372 hasConceptScore W4309341372C2779851693 @default.
- W4309341372 hasConceptScore W4309341372C33923547 @default.
- W4309341372 hasConceptScore W4309341372C41008148 @default.
- W4309341372 hasConceptScore W4309341372C45374587 @default.
- W4309341372 hasConceptScore W4309341372C459310 @default.
- W4309341372 hasConceptScore W4309341372C62520636 @default.
- W4309341372 hasConceptScore W4309341372C83283714 @default.
- W4309341372 hasConceptScore W4309341372C854659 @default.