Performance auto-tuning of GPU programs using machine learning
Performance auto-tuning of GPU programs using machine learning
批准号:
451889-2013
负责人:
Abdelrahman, Tarek
金额:
$2.9万
依托单位:
依托单位国家:
加拿大
项目类别:
Collaborative Research and Development Grants
财政年份:
2016
资助国家:
加拿大
项目状态:
已结题
起止时间:
2016-01-01 至 2017-12-31
中文摘要
智能手机和平板电脑等移动设备的软件应用程序出现了惊人的增长。这种增长增加了英特尔、AMD和高通等移动处理器制造商的压力,要求它们制造更强大、功耗更低的处理器。如今,这些制造商正在同一芯片上制造具有多核(CPU)和通用图形处理器(GPU)的处理器。GPU的使用很有吸引力,因为与CPU相比,GPU的速度可以提高10倍,而功率只有CPU的一小部分。然而,只有仔细地为GPU编写和调优程序,才能实现这一GPU优势--这是一个复杂且容易出错的过程。
英文摘要
There is a phenomenal growth in software applications for mobile devices such as smart phones and tablets. This growth increases the pressure on mobile processor manufacturers such as Intel, AMD and Qualcomm to make more powerful processors that consume less power. Today, these manufacturers are making processors with multiple cores (CPUs) combined with a general-purpose graphics-processing unit (GPU) on the same chip. The use of a GPU is attractive because the GPU can deliver a ten-fold increase in speed at a fraction of the power, compared to a CPU. However, this GPU benefit can be achieved only if programs are carefully written and tuned for the GPU--a process that is complex and error prone.
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