A case study of OpenCL on an Android mobile GPU

An observation in supercomputing in the past decade illustrates the transition of pervasive commodity products being integrated with the world's fastest system. Given today's exploding popularity of mobile devices, we investigate the possibilities for high performance mobile computing. Bec...

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Bibliographic Details
Published in2014 IEEE High Performance Extreme Computing Conference (HPEC) pp. 1 - 6
Main Authors Ross, James A., Richie, David A., Park, Song J., Shires, Dale R., Pollock, Lori L.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2014
Subjects
Android
Androids
Benchmark testing
Computer architecture
Graphics processing units
handheld GPU
Humanoid robots
Mobile communication
N-body
OpenCL
Performance evaluation
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Summary:An observation in supercomputing in the past decade illustrates the transition of pervasive commodity products being integrated with the world's fastest system. Given today's exploding popularity of mobile devices, we investigate the possibilities for high performance mobile computing. Because parallel processing on mobile devices will be the key element in developing a mobile and computationally powerful system, this study was designed to assess the computational capability of a GPU on a low-power, ARM-based mobile device. The methodology for executing computationally intensive benchmarks on a handheld mobile GPU is presented, including the practical aspects of working with the existing Android-based software stack and leveraging the OpenCL-based parallel programming model. The empirical results provide the performance of an OpenCL N-body benchmark and an auto-tuning kernel parameterization strategy. The achieved computational performance of the low-power mobile Adreno GPU is compared with a quad-core ARM, an ×86 Intel processor, and a discrete AMD GPU.
DOI:10.1109/HPEC.2014.7040987