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         "id"   : "https://puma.ub.uni-stuttgart.de/bibtex/25f74ed6faec00b5ef556cb54cc6d0c07/ishaandesai",         
         "tags" : [
            "coupling","julia","simulations","precice"
         ],
         
         "intraHash" : "5f74ed6faec00b5ef556cb54cc6d0c07",
         "interHash" : "3e8d3b3b9b2100facb8d5fdbb08f1884",
         "label" : "Coupling Julia-based Simulations via preCICE",
         "user" : "ishaandesai",
         "description" : "",
         "date" : "2021-12-14 13:05:59",
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         "year": "2021", 
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         "author": [ 
            "Pavel Kharitenko"
         ],
         "authors": [
         	
            	{"first" : "Pavel",	"last" : "Kharitenko"}
         ],
         "abstract": "The coupling library preCICE allows to couple single-physics solvers to partitioned\r\nmulti-physics simulations in a black-box fashion. preCICE is a C++ library, but it offers\r\nlanguage bindings to access the preCICE API from solvers written in other languages,\r\nsuch as C, Python, Fortran and MATLAB. The Julia Programming Language designed\r\nfor numerical computing is a strong candidate to be supported by preCICE. While Julia\r\nprovides a wide set of tools for interfacing with other languages, including C++, porting\r\na library such as preCICE that is made for High Performance Computing and runs on a\r\nhuge number of processes, requires little to no compromises. Multiple ways of wrapping\r\na C/C++ library are presented and implemented. In addition come Julia\u2019s own features,\r\nfor example the Distributed base library, that deviate from classic standards of known\r\nscientific languages. To test the bindings, two dummy solvers are coupled and presented in an example setup, with an outlook on further development.",
         "bibtexKey": "kharitenko2021coupling"

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