L-Bench: An Android benchmark set for low-power mobile GPUs

In recent years GPUs have become one of the most important components in mobile application processors (APs). Thus, performance measurement and analysis of mobile GPUs are crucial to mobile AP manufacturers, device manufacturers, graphics application programmers, and end users. However, it is hard t...

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Veröffentlicht in:Computers & graphics 2016-12, Vol.61, p.40-49
Hauptverfasser: Nah, Jae-Ho, Suh, Youngsun, Lim, Yeongkyu
Format: Artikel
Sprache:eng
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Zusammenfassung:In recent years GPUs have become one of the most important components in mobile application processors (APs). Thus, performance measurement and analysis of mobile GPUs are crucial to mobile AP manufacturers, device manufacturers, graphics application programmers, and end users. However, it is hard to analyze mobile GPUs in depth via existing high-level (with frames per second) or low-level benchmarks (with a fill rate, ALU performance, etc.). To bridge the gap between the benchmarks, we present a novel Android benchmark set for low-power GPUs, called L-Bench. This benchmark set consists of mid-level micro-benchmarks implemented on OpenGL ES 3.1, which are carefully chosen for different workloads. By analyzing the results, this benchmark suite provides not only frames per second of each benchmark but also performance of each GPU subsystem (geometry units, ALUs, texture mapping units, raster operations pipelines, caches/memory units, and tessellators) and overall GPU performance. For experiments, we perform our benchmark suite on five representative mobile devices that have different mobile GPUs, after that, we describe comprehensive analysis of each GPU architecture. [Display omitted] •A benchmark suite consisting of several mid-level micro-benchmarks is implemented on OpenGL ES 3.1 and AEP.•A methodology to measure performance of each GPU subsystem and overall GPU performance is presented.•Experiments on five mobile devices that have different mobile GPUs are performed and comprehensive analysis of each GPU architecture is described.
ISSN:0097-8493
1873-7684
DOI:10.1016/j.cag.2016.09.002