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A generic parallel pattern interface for stream and data processing
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Fastflow: High‐Level and Efficient Streaming on Multicore
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Comparing programming models for medical imaging on multi‐core systems
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A survey of algorithmic skeleton frameworks: high‐level structured parallel programming enablers
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Patterns and Skeletons for Parallel and Distributed Computing
inferredcites →https://doi.org/10.1007/978-3-319-49583-5_5openalex-snapshot
A C++ Generic Parallel Pattern Interface for Stream Processing
inferredcites →https://doi.org/10.1016/0198-0254(87)90391-8openalex-snapshot
Parallel and distributed computing
inferredcites →https://doi.org/10.1016/j.apnum.2014.12.008openalex-snapshot
Scientific computations on multi-core systems using different programming frameworks
inferredcites →https://doi.org/10.1109/cgo.2011.5764690openalex-snapshot
Intel's Array Building Blocks: A retargetable, dynamic compiler and embedded language
inferredcites →https://doi.org/10.1109/sbac-padw.2015.16openalex-snapshot
Kanga: A Skeleton-Based Generic Interface for Parallel Programming
inferredcites →https://doi.org/10.1109/trustcom.2015.623openalex-snapshot
Parallelizing High-Frequency Trading Applications by Using C++11 Attributes
inferredcites →https://doi.org/10.1177/1094342014567907openalex-snapshot
Parallel visual data restoration on multi-GPGPUs using stencil-reduce pattern
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Self‐adaptation on parallel stream processing: A systematic review
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Performance and programmability of GrPPI for parallel stream processing on multi-cores
inferred← citeshttps://doi.org/10.1016/j.cola.2022.101160openalex-snapshot
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