DocumentCode
1998997
Title
Tabulated Equations of State with a Many-tasking Execution Model
Author
Anderson, Matthew ; Brodowicz, Maciej ; Sterling, Thomas ; Kaiser, Hartmut ; Adelstein-Lelbach, Bryce
Author_Institution
Center for Res. in Extreme Scale Technol., Indiana Univ., Bloomington, IN, USA
fYear
2013
fDate
20-24 May 2013
Firstpage
1691
Lastpage
1699
Abstract
The addition of nuclear and neutrino physics to general relativistic fluid codes allows for a more realistic description of hot nuclear matter in neutron star and black hole systems. This additional microphysics requires that each processor have access to large tables of data, such as equations of state, and in large simulations, the memory required to store these tables locally can become excessive unless an alternative execution model is used. In this work we present relativistic fluid evolutions of a neutron star obtained using a message driven multi-threaded execution model known as ParalleX. The goal of this work is to reduce the negative performance impact of distributing the tables. We introduce a component based on the notion of a "future", or no blocking encapsulated delayed computation, for accessing large tables of data, including out of-core sized tables. The proposed technique does not impose substantial memory overhead and can hide increased network latency.
Keywords
astronomy computing; black holes; collections of physical data; equations of state; multi-threading; multiprocessing programs; neutron stars; relativistic fluid dynamics; ParalleX; black hole systems; data tables; many-tasking execution model; message driven multithreaded execution model; microphysics; network latency; neutrino physics; neutron star; nonblocking encapsulated delayed computation; nuclear matter; nuclear physics; out-of-core sized tables; relativistic fluid evolutions; table distribution; tabulated equations of state; Computational modeling; Earth Observing System; Equations; Instruction sets; Mathematical model; Neutrons; Runtime; Astrophysics applications; Futures; HPX; ParalleX;
fLanguage
English
Publisher
ieee
Conference_Titel
Parallel and Distributed Processing Symposium Workshops & PhD Forum (IPDPSW), 2013 IEEE 27th International
Conference_Location
Cambridge, MA
Print_ISBN
978-0-7695-4979-8
Type
conf
DOI
10.1109/IPDPSW.2013.162
Filename
6651067
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