Interactive design of GPU-accelerated Image Data Flow Graphs and cross-platform deployment using multi-lingual code generation

2020 ◽  
Author(s):  
Mariana De Niz
Keyword(s):  
Code Generation ◽  
Data Flow ◽  
Image Data ◽  
Interactive Design ◽  
Cross Platform ◽  
Data Flow Graphs ◽  
Flow Graphs

scholarly journals Interactive design of GPU-accelerated Image Data Flow Graphs and cross-platform deployment using multi-lingual code generation

2020 ◽  
Author(s):  
Robert Haase ◽  
Akanksha Jain ◽  
Stéphane Rigaud ◽  
Daniela Vorkel ◽  
Pradeep Rajasekhar ◽  
...  
Keyword(s):  
Image Processing ◽  
Image Analysis ◽  
Code Generation ◽  
Graphics Processing Units ◽  
Data Flow ◽  
Fluorescent Microscopy ◽  
Image Data ◽  
General Applicability ◽  
Data Flow Graphs ◽  
Flow Graphs

AbstractModern life science relies heavily on fluorescent microscopy and subsequent quantitative bio-image analysis. The current rise of graphics processing units (GPUs) in the context of image processing enables batch processing large amounts of image data at unprecedented speed. In order to facilitate adoption of this technology in daily practice, we present an expert system based on the GPU-accelerated image processing library CLIJ: The CLIJ-assistant keeps track of which operations formed an image and suggests subsequent operations. It enables new ways of interaction with image data and image processing operations because its underlying GPU-accelerated image data flow graphs (IDFGs) allow changes to parameters of early processing steps and instantaneous visualization of their final results. Operations, their parameters and connections in the IDFG are stored at any point in time enabling the CLIJ-assistant to offer an undo-function for virtually unlimited rewinding parameter changes. Furthermore, to improve reproducibility of image data analysis workflows and interoperability with established image analysis platforms, the CLIJ-assistant can generate code from IDFGs in programming languages such as ImageJ Macro, Java, Jython, JavaScipt, Groovy, Python and C++ for later use in ImageJ, Fiji, Icy, Matlab, QuPath, Jupyter Notebooks and Napari. We demonstrate the CLIJ-assistant for processing image data in multiple scenarios to highlight its general applicability. The CLIJ-assistant is open source and available online: https://clij.github.io/assistant/

scholarly journals Inductive data flow graphs

2013 ◽  
Vol 48 (1) ◽  
pp. 129-142 ◽  
Author(s):  
Azadeh Farzan ◽  
Zachary Kincaid ◽  
Andreas Podelski
Keyword(s):  
Data Flow ◽  
Data Flow Graphs ◽  
Flow Graphs

Liveness and Boundedness of Synchronous Data Flow Graphs

2006 ◽  
Author(s):  
A.H. Ghamarian ◽  
M.C.W. Geilen ◽  
T. Basten ◽  
B.D. Theelen ◽  
M.R. Mousavi ◽  
...  
Keyword(s):  
Data Flow ◽  
Data Flow Graphs ◽  
Synchronous Data Flow ◽  
Flow Graphs
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