Mars: a MapReduce framework on graphics processors

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 CPUs. Compared with commodity 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 hundreds of processors, and evaluated it in comparison with Phoenix, the state-ofthe-art MapReduce framework on multi-core processors. 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. Ad...

• Type: Conference
• Year: 2008
• Where: IEEEPACT
• Authors: Bingsheng He, Wenbin Fang, Qiong Luo, Naga K. Govindaraju, Tuyong Wang
• Keywords: Hardware, Harness Gpu Power, IEEEPACT 2008, MapReduce Framework, NVIDIA G80 GPU