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2. Visibility Algorithms for Dynamic Dependence Analysis and Distributed Coherence
 
 # Visibility Algorithms for Dynamic Dependence Analysis and Distributed Coherence

  ![Publication image](/sites/default/files/styles/wide/public/default_images/default.jpeg?itok=qUFsuJCP "Publication image")

 Implicitly parallel programming systems must solve the joint problems of dependence analysis and coherence to ensure apparently-sequential semantics for applications run on distributed memory machines. Solving these problems in the presence of data-dependent control flow and arbitrary aliasing is a challenge that most existing systems eschew by compromising the expressivity of their programming models and/or the performance of their implementations. We demonstrate a general class of solutions to these problems via a reduction to the visibility problem from computer graphics.



 ## Authors



[Michael Bauer](/index.php/person/mike-bauer)

Elliott Slaughter (SLAC National Accelerator Laboratory)

Sean Treichler (NVIDIA)

Wonchan Lee (NVIDIA)

[Michael Garland](/index.php/person/michael-garland)

Alex Aiken (Stanford University)

 

 

 ## Publication Date



Monday, February 27, 2023

 

 ## Published in



[PPoPP](https://conf.researchr.org/home/ppopp-2023)

 

 ## Research Area



[Computer Graphics](/index.php/research-area/computer-graphics)

[High Performance Computing](/index.php/research-area/high-performance-computing)

[Programming Languages, Systems and Tools](/index.php/research-area/programming-languages-systems)

 

 

 ## Uploaded Files



[Visibility\_PPOPP\_2023.pdf](https://d1qx31qr3h6wln.cloudfront.net/publications/Visibility_PPOPP_2023_1.pdf "Open file in new window")2.26 MB