QIG:Quantifying the Importance and Interaction of GPGPU Architecture Parameters
文献类型：期刊论文
| 作者 | Zhibin Yu; Jing Wang; Lieven Eeckhout; Chengzhong Xu; Jingwen Leng; Vijay Janapa Reddi |
| 刊名 | IEEE Transactions on Computer-aided design of integrated circuits and system.
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| 出版日期 | 2017 |
| 文献子类 | 期刊论文 |
| 英文摘要 | Graphic Processing Units (GPUs) are widely used for general-purpose computing — so-called GPGPU computing. GPUs feature a large number of architecture parameters, resulting in a huge design space. To quickly explore this design space and identify the optimum architecture for a group of widely used computing kernels, it is critical to know how important each parameter is and how strongly these parameters interact with each other. This paper proposes an ensemble-learning based approach, called QIG, to quantify the importance of architecture parameters and their interactions with respect to performance. QIG employs a stochastic gradient boosted regression tree (SGBRT) to construct performance models using performance data from a random set of GPU architectures. Leveraging these models, QIG observes the impact of each architecture parameter on performance, and calculates its importance and interaction intensity with other parameters. Using 25 widely used GPGPU kernels, we demonstrate that QIG accurately ranks the importance and interaction of GPU architecture parameters while the previously proposed Plackett-Burman design does not. Moreover, we show that QIG leads to a substantially more accurate performance model compared to prior work, including Starchart and approaches using ANNs and SVMs: average error of 4.2% for QIG versus 23+% for prior work. Finally, QIG reveals a number of interesting insights for GPU architectures running GPGPU workloads. |
| URL标识 | 查看原文 |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/12532]  |
| 专题 | 深圳先进技术研究院_数字所 |
| 作者单位 | IEEE Transactions on Computer-aided design of integrated circuits and system. |
| 推荐引用方式 GB/T 7714 | Zhibin Yu,Jing Wang,Lieven Eeckhout,et al. QIG:Quantifying the Importance and Interaction of GPGPU Architecture Parameters[J]. IEEE Transactions on Computer-aided design of integrated circuits and system.,2017. |
| APA | Zhibin Yu,Jing Wang,Lieven Eeckhout,Chengzhong Xu,Jingwen Leng,&Vijay Janapa Reddi.(2017).QIG:Quantifying the Importance and Interaction of GPGPU Architecture Parameters.IEEE Transactions on Computer-aided design of integrated circuits and system.. |
| MLA | Zhibin Yu,et al."QIG:Quantifying the Importance and Interaction of GPGPU Architecture Parameters".IEEE Transactions on Computer-aided design of integrated circuits and system. (2017). |
入库方式： OAI收割
来源：深圳先进技术研究院
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