Abstract
This paper discusses the Data Mover, an abstraction for expressing machine-independent customized communication algorithms arising in block-structured computations. The Data Mover achieves performance that is competitive with hand-coding in MPI, but enables application-specific optimization to be expressed using intuitive geometric set operations that encapsulate low-level details.
Keywords
- Data Mover
- Message Passing Interface
- Member Function
- Multidimensional Array
- Message Passing Interface Implementation
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Baden, S.B., Fink, S.J. (2000). The Data Mover: A Machine-Independent Abstraction for Managing Customized Data Motion. In: Carter, L., Ferrante, J. (eds) Languages and Compilers for Parallel Computing. LCPC 1999. Lecture Notes in Computer Science, vol 1863. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44905-1_21
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DOI: https://doi.org/10.1007/3-540-44905-1_21
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