Hancheng Wu

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GPUs have been widely used to accelerate computations exhibiting simple patterns of parallelism -- such as flat or two-level parallelism -- and a degree of parallelism that can be statically determined based on the size of the input dataset. However, the effective use of GPUs for algorithms exhibiting complex patterns of parallelism, possibly known only at(More)
The effective deployment of applications exhibiting irregular nested parallelism on GPUs is still an open problem. A naïve mapping of irregular code onto the GPU hardware often leads to resource underutilization and, thereby, limited performance. In this work, we focus on two computational patterns exhibiting nested parallelism: irregular nested(More)
Graphics Processing Units (GPUs) have been used in general purpose computing for several years. The newly introduced Dynamic Parallelism feature of Nvidia's Kepler GPUs allows launching kernels from the GPU directly. However, the naïve use of this feature can cause a high number of nested kernel launches, each performing limited work, leading to GPU(More)
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