Mars: a MapReduce framework on graphics processors Export

@inproceedings{citeulike:4009779, abstract = {We design and implement Mars, a MapReduce framework, on graphics processors (GPUs). MapReduce is a distributed programming framework originally proposed by Google for the ease of development of web search applications on a large number of commodity CPUs. Compared with CPUs, GPUs have an order of magnitude higher computation power and memory bandwidth, but are harder to program since their architectures are designed as a special-purpose co-processor and their programming interfaces are typically for graphics applications. As the first attempt to harness GPU's power for MapReduce, we developed Mars on an NVIDIA G80 GPU, which contains over one hundred processors, and evaluated it in comparison with Phoenix, the state-of-the-art MapReduce framework on multi-core CPUs. Mars hides the programming complexity of the GPU behind the simple and familiar MapReduce interface. It is up to 16 times faster than its CPU-based counterpart for six common web applications on a quad-core machine.}, address = {New York, NY, USA}, author = {He, Bingsheng and Fang, Wenbin and Luo, Qiong and Govindaraju, Naga K. and Wang, Tuyong}, booktitle = {PACT '08: Proceedings of the 17th international conference on Parallel architectures and compilation techniques}, citeulike-article-id = {4009779}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1454115.1454152}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/1454115.1454152}, doi = {10.1145/1454115.1454152}, isbn = {978-1-60558-282-5}, keywords = {framework, gpgpu, mapreduce, mars}, location = {Toronto, Ontario, Canada}, pages = {260--269}, posted-at = {2009-02-05 00:20:51}, priority = {4}, publisher = {ACM}, title = {Mars: a MapReduce framework on graphics processors}, url = {http://dx.doi.org/10.1145/1454115.1454152}, year = {2008} }

TY - CONF ID - citeulike:4009779 L3 - citeulike-article-id:4009779 N2 - We design and implement Mars, a MapReduce framework, on graphics processors (GPUs). MapReduce is a distributed programming framework originally proposed by Google for the ease of development of web search applications on a large number of commodity CPUs. Compared with CPUs, GPUs have an order of magnitude higher computation power and memory bandwidth, but are harder to program since their architectures are designed as a special-purpose co-processor and their programming interfaces are typically for graphics applications. As the first attempt to harness GPU's power for MapReduce, we developed Mars on an NVIDIA G80 GPU, which contains over one hundred processors, and evaluated it in comparison with Phoenix, the state-of-the-art MapReduce framework on multi-core CPUs. Mars hides the programming complexity of the GPU behind the simple and familiar MapReduce interface. It is up to 16 times faster than its CPU-based counterpart for six common web applications on a quad-core machine. CY - Toronto, Ontario, Canada SN - 978-1-60558-282-5 AD - New York, NY, USA EP - 269 TI - Mars: a MapReduce framework on graphics processors PB - ACM T2 - PACT '08: Proceedings of the 17th international conference on Parallel architectures and compilation techniques SP - 260 KW - framework KW - gpgpu KW - mapreduce KW - mars AU - He, Bingsheng AU - Fang, Wenbin AU - Luo, Qiong AU - Govindaraju, Naga AU - Wang, Tuyong PY - 2008/// UR - http://dx.doi.org/10.1145/1454115.1454152 ER -