OpenCL-Based Mobile GPGPU Benchmarking: Methods and Challenges
Qualcomm
International Workshop on OpenCL (IWOCL), 2016
@inproceedings{Aviv_Wang_iwocl2016,
title={OpenCL-Based Mobile GPGPU Benchmarking: Methods and Challenges},
author={Aviv, Rotem and Wang, Guohui},
booktitle={Proc. International Workshop on OpenCL (IWOCL)},
pages={},
month={Apr.},
year={2016},
organization={ACM}
}
Benchmarking general-purpose computing on graphics processing unit (GPGPU) aims to profile and compare performance across different devices. Due to the low-level nature of most GPGPU APIs, GPGPU benchmarks are also useful for architectural exploration and program optimization. This can be challenging in mobile devices due to lack of underlying hardware details and limited profiling capabilities in some platforms. Measuring the performance of mobile GPU by executing benchmarks covering major hardware and software features can reveal the strength and weakness of a GPGPU system, enable better program optimization and make automatic performance tuning possible.
In this paper, we will describe several design methods of OpenCL-based mobile GPGPU benchmarking, and discuss key issues that one may encounter during development. We will also present design tips and guidelines to achieve more ”fair” and accurate benchmarking results.
April 22, 2016 by lanshan317
