2012
DOI: 10.1109/mc.2012.257
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Can GPGPU Programming Be Liberated from the Data-Parallel Bottleneck?

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Cited by 33 publications
(16 citation statements)
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“…Steffen et al [34] propose the idea of dynamic micro-kernel architecture for global rendering algorithm which supports dynamically spawning threads as a new warp to execute a subsection of the parent threads code. Orr et al [29] design a task aggregation framework on GPU based on the channel abstraction proposed by Gaster et al [14]. Each channel is defined as a finite queue in virtual memory (global memory space that is visible to both CPU and GPU) whose elements are dynamically generated tasks that execute the same kernel function.…”
Section: Related Workmentioning
confidence: 99%
“…Steffen et al [34] propose the idea of dynamic micro-kernel architecture for global rendering algorithm which supports dynamically spawning threads as a new warp to execute a subsection of the parent threads code. Orr et al [29] design a task aggregation framework on GPU based on the channel abstraction proposed by Gaster et al [14]. Each channel is defined as a finite queue in virtual memory (global memory space that is visible to both CPU and GPU) whose elements are dynamically generated tasks that execute the same kernel function.…”
Section: Related Workmentioning
confidence: 99%
“…The global memory often acts as the performance bottleneck even for most data-parallel GPU kernels [2][3][4][5][6][7][8].…”
Section: Related Workmentioning
confidence: 99%
“…We contend that an optimal mapping probably adheres to the braided parallelism paradigm [19], in which data parallel bits (e.g. the construct_tour phase) are interwoven with serial or weakly parallel ones (i.e.…”
Section: The Max-min Ant System and Its Application To The Tspmentioning
confidence: 99%