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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/5252Full metadata record
| ???org.dspace.app.webui.jsptag.ItemTag.dcfield??? | Value | Language |
|---|---|---|
| dc.contributor.advisor | 劉邦鋒(Pangfeng Liu) | |
| dc.contributor.author | Wei-Shu Hung | en |
| dc.contributor.author | 洪偉書 | zh_TW |
| dc.date.accessioned | 2021-05-15T17:54:24Z | - |
| dc.date.available | 2015-07-29 | |
| dc.date.available | 2021-05-15T17:54:24Z | - |
| dc.date.copyright | 2014-07-29 | |
| dc.date.issued | 2014 | |
| dc.date.submitted | 2014-07-25 | |
| dc.identifier.citation | 1] Amd. http://www.amd.com/.
[2] Amd app sdk. http://developer.amd.com/tools-and-sdks/opencl-zone/opencl-toolssdks/ amd-accelerated-parallel-processing-app-sdk/. [3] Android ndk. https://developer.android.com/tools/sdk/ndk/index.html. [4] Cuda. http://www.nvidia.com/content/cuda/cuda-toolkit.html. [5] Errison mobility report on the pulse of the networked society. http://www.ericsson.com/mobility-report. [6] Intel. http://www.intel.com/. [7] Json. http://www.json.org/. [8] Net index. http://www.netindex.com/. [9] Nvidia. http://www.nvidia.com/. [10] Sony android opencl sample. http://developer.sonymobile.com/knowledgebase/ tutorials/android tutorial/boost-the-performance-of-your-android-app-with-opencl/. [11] Amazon elastic compute cloud. http://aws.amazon.com/ec2/. [12] S. Che, M. Boyer, J. Meng, D. Tarjan, J. W. Sheaffer, and K. Skadron. A performance study of general-purpose applications on graphics processors using cuda. J. Parallel Distrib. Comput., 68(10):1370–1380, Oct. 2008. [13] B.-G. Chun, S. Ihm, P. Maniatis, M. Naik, and A. Patti. Clonecloud: Elastic execution between mobile device and cloud. In Proceedings of the Sixth Conference on Computer Systems, EuroSys ’11, pages 301–314, New York, NY, USA, 2011. ACM. [14] E. Cuervo, A. Balasubramanian, D.-k. Cho, A. Wolman, S. Saroiu, R. Chandra, and P. Bahl. Maui: Making smartphones last longer with code offload. In Proceedings of the 8th International Conference on Mobile Systems, Applications, and Services, MobiSys ’10, pages 49–62, New York, NY, USA, 2010. ACM. [15] J. Dean and S. Ghemawat. Mapreduce: Simplified data processing on large clusters. Commun. ACM, 51(1):107–113, Jan. 2008. [16] K. O. W. Group. The OpenCL Specification Version: 1.1 Document Revision: 44, 2011. [17] D. T. Hoang, C. Lee, D. Niyato, and P. Wang. A survey of mobile cloud computing: architecture, applications, and approaches. Wireless Communications and Mobile Computing, 13(18):1587–1611, 2013. [18] G. Huerta-Canepa and D. Lee. A virtual cloud computing provider for mobile devices. In Proceedings of the 1st ACM Workshop on Mobile Cloud Computing & Services: Social Networks and Beyond, MCS ’10, pages 6:1–6:5, New York, NY, USA, 2010. ACM. [19] D. Luebke, M. Harris, N. Govindaraju, A. Lefohn, M. Houston, J. Owens, M. Segal, M. Papakipos, and I. Buck. Gpgpu: General-purpose computation on graphics hardware. In Proceedings of the 2006 ACM/IEEE Conference on Supercomputing, SC ’06, New York, NY, USA, 2006. ACM. [20] E. E. Marinelli. Hyrax: cloud computing on mobile devices using mapreduce. Technical report, DTIC Document, 2009. [21] J. Owens, M. Houston, D. Luebke, S. Green, J. Stone, and J. Phillips. Gpu computing. Proceedings of the IEEE, 96(5):879–899, May 2008. [22] Z. Sanaei, S. Abolfazli, A. Gani, and R. Buyya. Heterogeneity in mobile cloud computing: Taxonomy and open challenges. Communications Surveys Tutorials, IEEE, 16(1):369–392, First 2014. [23] M. Satyanarayanan. Pervasive computing: vision and challenges. Personal Communications, IEEE, 8(4):10–17, Aug 2001. [24] J. E. Stone, D. Gohara, and G. Shi. Opencl: A parallel programming standard for heterogeneous computing systems. IEEE Des. Test, 12(3):66–73, May 2010. [25] T. White. Hadoop: The Definitive Guide. O’Reilly Media, Inc., 1st edition, 2009. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/5252 | - |
| dc.description.abstract | Nowadays, mobile devices are suffering from limited computational resource. To increase
capabilities of mobile devices, many efforts have been made to offload computation from mobile devices to resourceful servers. However, most of the approaches are only capable of offloading computation to CPUs. Recently, GPUs have received a lot of attention from the scientific community. Indeed, the exceptional parallel computing capabilities of GPUs can be used to accelerate different types of applications. In this thesis, we propose a computation offloading framework based on OpenCL – a standard for GPU computing. Our framework transparently offloads OpenCL workloads from mobile devices to an available OpenCL compatible device. We deployed our framework on real machines and conducted evaluation experiments using various OpenCL programs including basic matrix computations, an image processing Android app and benchmarks from AMD. The program achieves up to 50.3X speedup by remote offloading compared to the local execution using CPU. | en |
| dc.description.provenance | Made available in DSpace on 2021-05-15T17:54:24Z (GMT). No. of bitstreams: 1 ntu-103-R01922071-1.pdf: 697483 bytes, checksum: e89a0fe175a60d09f002ffc7715b375f (MD5) Previous issue date: 2014 | en |
| dc.description.tableofcontents | Certificate i
Acknowledgement ii Chinese Abstract iii Abstract iv 1 Introduction 1 2 RelatedWork 3 2.1 Computation Offloading Research for Mobile Device . . . . . . . . . . . . . . . 3 2.2 OpenCL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.2.1 Platform Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.2.2 Execution Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 3 System Architecture 7 3.1 System Components . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 3.1.1 OpenCL Client . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 3.1.2 OpenCL Server . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 3.1.3 OpenCL Manager . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 3.2 System Flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 4 Implementation 12 4.1 OpenCL Client . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 4.2 OpenCL Server . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 4.3 OpenCL Manager . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 5 Experiments 16 5.1 Experimental Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 5.2 Experiment Result . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 6 Conclusion 21 Bibliography 22 | |
| dc.language.iso | en | |
| dc.subject | GPU | zh_TW |
| dc.subject | 運算移轉 | zh_TW |
| dc.subject | 普及運算 | zh_TW |
| dc.subject | 行動雲端運算 | zh_TW |
| dc.subject | OpenCL | zh_TW |
| dc.subject | GPGPU | zh_TW |
| dc.subject | GPGPU | en |
| dc.subject | OpenCL | en |
| dc.subject | Computation Offloading | en |
| dc.subject | GPU | en |
| dc.subject | Pervasive Computing | en |
| dc.subject | Mobile Cloud Computing | en |
| dc.title | 智慧型行動裝置OpenCL運算移轉框架 | zh_TW |
| dc.title | OpenCL Computation Offloading Framework on Mobile Device | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 102-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.coadvisor | 吳真貞(Jan-Jan Wu) | |
| dc.contributor.oralexamcommittee | 徐慰中(Wei-Chung Hsu) | |
| dc.subject.keyword | OpenCL,GPU,GPGPU,行動雲端運算,普及運算,運算移轉, | zh_TW |
| dc.subject.keyword | OpenCL,GPU,GPGPU,Mobile Cloud Computing,Pervasive Computing,Computation Offloading, | en |
| dc.relation.page | 23 | |
| dc.rights.note | 同意授權(全球公開) | |
| dc.date.accepted | 2014-07-25 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 資訊工程學研究所 | zh_TW |
| Appears in Collections: | 資訊工程學系 | |
Files in This Item:
| File | Size | Format | |
|---|---|---|---|
| ntu-103-1.pdf | 681.14 kB | Adobe PDF | View/Open |
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