Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The growing scale of concurrency requires automated abstraction techniques to cut down the effort in concurrent system analysis. ,  show that the high degree of behavioral symmetry present in GPU programs allows CUDA race detection to be dramatically simplified through abstraction. Our abstraction techniques is one of  automatically  creating  parametric flows ---control-flow equivalence classes of threads that diverge in the same manner---and checking for data races only across a pair of threads per parametric flow.  have implemented this approach as an extension of our recently proposed GKLEE symbolic analysis framework and show that all our previous results are dramatically improved in that (i) the parametric flow-based analysis takes far less time, and (ii) because of the much higher scalability of the analysis,  can detect even more data race situations that re previously missed by GKLEE because it was forced to downscale examples to limit analysis complexity. Moreover, the parametric flow-based analysis is applicable to other programs with SPMD models.
['Peng Li', 'Guodong Li', 'Ganesh Gopalakrishnan']
I am writing a research paper on a idea Parametric flows: automated behavior equivalencing for symbolic analysis of races in CUDA programs
[{"from": "human", "value": "I am writing a research paper on a idea Parametric flows: automated behavior equivalencing for symbolic analysis of races in CUDA programs"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The growing scale of concurrency requires automated abstraction techniques to cut down the effort in concurrent system analysis. ,  show that the high degree of behavioral symmetry present in GPU programs allows CUDA race detection to be dramatically simplified through abstraction. Our abstraction techniques is one of  automatically  creating  parametric flows ---control-flow equivalence classes of threads that diverge in the same manner---and checking for data races only across a pair of threads per parametric flow.  have implemented this approach as an extension of our recently proposed GKLEE symbolic analysis framework and show that all our previous results are dramatically improved in that (i) the parametric flow-based analysis takes far less time, and (ii) because of the much higher scalability of the analysis,  can detect even more data race situations that re previously missed by GKLEE because it was forced to downscale examples to limit analysis complexity. Moreover, the parametric flow-based analysis is applicable to other programs with SPMD models."}]