Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Renato B. Hoffmann"'
Publikováno v:
International Journal of Parallel Programming. 50:454-485
Publikováno v:
The Journal of Supercomputing. 78:7655-7676
Publikováno v:
Anais da XXII Escola Regional de Alto Desempenho da Região Sul (ERAD-RS 2022).
Stream processing applications process raw data-flows to reveal insightful information. Efficiently coordinating the requirements of these applications is a challenge. We propose investigating high-level software solutions for these applications to a
Publikováno v:
Anais do XXII Simpósio em Sistemas Computacionais de Alto Desempenho (WSCAD 2021).
Profiling tools are essential to understand the behavior of parallel applications and assist in the optimization process. However, tools such as Perf generate a large amount of data. This way, they require significant storage space, which also compli
Publikováno v:
Journal of Computer Languages. 73:101160
Publikováno v:
Anais da XXI Escola Regional de Alto Desempenho da Região Sul (ERAD RS 2021).
OpenMP é complexo quando usado para desenvolver aplicações de fluxo de dados. Com o objetivo de mitigar essa dificuldade, foi utilizada uma metodologia existente, chamada SPar, para aumentar o nível de abstração. Portanto, foram utilizadas an
Publikováno v:
SBLP
Data generation, collection, and processing is an important workload of modern computer architectures. Stream or high-intensity data flow applications are commonly employed in extracting and interpreting the information contained in this data. Due to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::03e712825bc2a093dc5cc9fa3d36d97d
http://hdl.handle.net/11568/1080447
http://hdl.handle.net/11568/1080447
Publikováno v:
Journal of Computer Languages. 65:101054
This work aims at contributing with a structured parallel programming abstraction for Rust in order to provide ready-to-use parallel patterns that abstract low-level and architecture-dependent details from application programmers. We focus on stream
It is often a challenge to keep input/output tasks/results in order for parallel computations over data streams, particularly when stateless task operators are replicated to increase parallelism when there are irregular tasks. Maintaining input/outpu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a215cb6c5683f26a7507034df6c4a1ad
http://hdl.handle.net/11568/952756
http://hdl.handle.net/11568/952756