Danelutto et al., 2018 - Google Patents

Data stream processing via code annotations

Danelutto et al., 2018

Document ID: 7678263820168208124
Author: Danelutto M; De Matteis T; Mencagli G; Torquati M
Publication year: 2018
Publication venue: The Journal of Supercomputing

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Time-to-solution is an important metric when parallelizing existing code. The REPARA approach provides a systematic way to instantiate stream and data parallel patterns by annotating the sequential source code with C++ 11 attributes. Annotations are automatically …

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 [O-2].[O-2].[O-2].[O-2].[Fe+3].[Fe+3].[Zn+2] 0 abstract description 37

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Publication	Publication Date	Title
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Brown et al.	2014	Cost-directed refactoring for parallel Erlang programs
Danelutto et al.	2018	Data stream processing via code annotations
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US12039305B2 (en)	2024-07-16	Method for compilation, electronic device and storage medium
Huchant et al.	2016	Automatic OpenCL task adaptation for heterogeneous architectures
Jacob et al.	2019	Python programmers have GPUs too: automatic Python loop parallelization with staged dependence analysis
Saumya et al.	2022	DARM: control-flow melding for SIMT thread divergence reduction
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US20170147943A1 (en)	2017-05-25	Global data flow optimization for machine learning programs
Vogel et al.	2019	Minimizing self-adaptation overhead in parallel stream processing for multi-cores
Beck et al.	1990	Static scheduling for dynamic dataflow machines
Garcia et al.	2020	Challenging the abstraction penalty in parallel patterns libraries: Adding FastFlow support to GrPPI
Danelutto et al.	2018	State access patterns in stream parallel computations
US9152543B1 (en)	2015-10-06	Symbolic execution with automatic abstractions
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US11144290B2 (en)	2021-10-12	Method and apparatus for enabling autonomous acceleration of dataflow AI applications
Muller et al.	2024	Modeling and analyzing evaluation cost of CUDA kernels
Malakonakis et al.	2018	HLS algorithmic explorations for HPC execution on reconfigurable hardware-ECOSCALE
Schleier-Smith et al.	2016	Restream: Accelerating backtesting and stream replay with serial-equivalent parallel processing
Alefragis et al.	2018	Mapping and scheduling hard real time applications on multicore systems-the argo approach
Saumya et al.	2021	DARM: Control-Flow Melding for SIMT Thread Divergence Reduction--Extended Version
de Mello Junior et al.	2020	Fluid computing: Interest-based communication in dataflow/multiset rewriting computing
Jradi et al.	2018	A GPU-Based Parallel Reduction Implementation

Danelutto et al., 2018 - Google Patents

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