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	Efficient kernel management on GPUs
	Li, Xiuhong ; Liang, Yun
	2016
英文摘要	As the complexity of applications continues to grow, each new generation of GPUs has been equipped with advanced architectural features and more resources to sustain its performance acceleration capability. Recent GPUs have been featured with concurrent kernel execution, which is designed to improve the resource utilization by executing multiple kernels simultaneously. However, prior systems only achieve limited performance improvement as they do not optimize the thread-level parallelism (TLP) and model the resource contention for the concurrently executing kernels. In this paper, we design a framework that optimizes the performance and energy-efficiency for multiple kernel execution on GPUs. It employs two key techniques. First, we develop an algorithm to adjust the TLP for the concurrently executing kernels. Second, we employ cache bypassing to mitigate the cache contention. Experiments indicate that our framework can improve performance by 1.42X on average (energy-efficiency by 1.33X on average), compared with the default concurrent kernel execution framework. ? 2016 EDAA.; EI; 85-90
语种	英语
出处	19th Design, Automation and Test in Europe Conference and Exhibition, DATE 2016
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/436196]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Li, Xiuhong,Liang, Yun. Efficient kernel management on GPUs. 2016-01-01.

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