2026-04-27T21:31:38Zhttps://uvadoc.uva.es/oai/requestoai:uvadoc.uva.es:10324/704452025-01-30T10:20:55Zcom_10324_1165com_10324_931com_10324_894col_10324_1337
UVaDOC
author
Moreton Fernández, Ana
author
González Escribano, Arturo
author
Llanos Ferraris, Diego Rafael
2024-10-04T15:55:25Z
2024-10-04T15:55:25Z
2016
Intl. Symp. on High Level Parallel Programming and Applications (HLPP 2016), Münster, Germany.
https://uvadoc.uva.es/handle/10324/70445
10.5281/zenodo.11213594
Programming for distributed-memory systems imposes specific challenges. In these systems, minimizing synchronization and communication overheads is key for performance improvement. A typical approach is to use a message-passing paradigm to exploit static partition policies and to generate coarse-grain computations with aggregated communication phases. However, irregular or data-dependent programs that need dynamic data redistributions become more complicated to develop and debug. In this paper we present four abstract array distribution operators that allow to efficiently implement programs on distributed-memory systems, making the data partition, relocation, and data movement transparent to the programmer. Our experimental results show that our approach does not imply significant overheads, while achieving good scalability for combinations of data-dependent, irregular, or recursive parallel structures on distributed-memory systems.
eng
Informática
Four abstract array distribution operators
info:eu-repo/semantics/conferenceObject
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URL
https://uvadoc.uva.es/bitstream/10324/70445/1/hlpp-v2.pdf
File
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application/pdf
hlpp-v2.pdf