- author = "Arian Maghazeh and Unmesh D. Bordoloi and Petru Eles and Zebo Peng",
- title = "General purpose computing on low-power embedded {GPUs}: Has it come of age?",
- booktitle = "2013 International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation (SAMOS XIII)",
- year = "2013",
- editor = "H. Jeschke",
- address = "Samos, Greece",
- month = "15-18 " # jul,
- publisher = "IEEE",
- keywords = "genetic algorithms, genetic programming, GPU, GPGPU, OpenCL, ARM Cortex A9 Vivante GC2000 GPU, Tesla M2050, Intertwined Spiral problem, Rijndael, bitcount , convolution, pattern matching, energy consumption",
- isbn13 = "978-1-4799-0103-6",
-
DOI = "
doi:10.1109/SAMOS.2013.6621099",
- size = "10 pages",
- abstract = "In this paper we evaluate the promise held by low-power GPUs for non-graphic workloads that arise in embedded systems. Towards this, we map and implement 5 benchmarks, that find utility in very different application domains, to an embedded GPU. Our results show that apart from accelerated performance, embedded GPUs are promising also because of their energy efficiency which is an important design goal for battery-driven mobile devices. We show that adopting the same optimization strategies as those used for programming high-end GPUs might lead to worse performance on embedded GPUs. This is due to restricted features of embedded GPUs, such as, limited or no user-defined memory, small instruction-set, limited number of registers, among others. We propose techniques to overcome such challenges, e.g., by distributing the workload between GPUs and multi-core CPUs, similar to the spirit of heterogeneous computation.",
-
notes = "Dept. of Comput. & Inf. Sci., Linkopings Univ.,
Linkopings, Sweden
Also known as \cite{6621099}",
