Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The global scheduler of a current GPU distributes thread blocks to symmetric multiprocessors (SM), which schedule threads for execution with the granularity of a warp. Threads in a warp execute the same code path in lockstep, which potentially leads to a large amount of wasted cycles for divergent control flow. In order to overcome this general issue of SIMT architectures,  propose techniques to relax divergence on the fly within a computation kernel in order to achieve a much higher total utilization of processing cores.  propose techniques for branch and loop divergence (which may also be combined) switching to suitable tasks during a GPU kernel run every time divergence occurs. Our newly introduced techniques can easily be applied to arbitrary iterative algorithms and  evaluate the performance and effectiveness of our approach exemplarily via synthetic and real world applications.
['Steffen Frey', 'Guido Reina', 'Thomas Ertl']
I am writing a research paper on a idea SIMT Microscheduling: Reducing Thread Stalling in Divergent Iterative Algorithms
[{"from": "human", "value": "I am writing a research paper on a idea SIMT Microscheduling: Reducing Thread Stalling in Divergent Iterative Algorithms"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The global scheduler of a current GPU distributes thread blocks to symmetric multiprocessors (SM), which schedule threads for execution with the granularity of a warp. Threads in a warp execute the same code path in lockstep, which potentially leads to a large amount of wasted cycles for divergent control flow. In order to overcome this general issue of SIMT architectures,  propose techniques to relax divergence on the fly within a computation kernel in order to achieve a much higher total utilization of processing cores.  propose techniques for branch and loop divergence (which may also be combined) switching to suitable tasks during a GPU kernel run every time divergence occurs. Our newly introduced techniques can easily be applied to arbitrary iterative algorithms and  evaluate the performance and effectiveness of our approach exemplarily via synthetic and real world applications."}]