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1 IntroductionrnGraph processing has received significant attention for its abil-ity to cope with large-scale and complex unstructured data in the real-world.However,most of the graph processing appli-cations exhibit an irregular memory access pattern which leads to a poor locality in the memory access stream[1],and[2]re-veals that the sub-optimal use of the cache hierarchy can result in the CPU only works in the range of 10％ to 45％ of the over-all graph processing time.Furthermore,the operating charac-teristics are discrepant in various graph applications[3],which cause the efficiency of existing graph processing frameworks is bogged down by a single memory organization.Consequently,how to design an efficient memory data organization strategy is key to accelerating graph processing.